Updated on 2024/10/10

写真a

 
Nojima Yusuke
 
Organization
Graduate School of Informatics Department of Core Informatics Professor
School of Engineering Department of Information Science
Title
Professor
Affiliation
Institute of Informatics
Contact information
メールアドレス
Affiliation campus
Nakamozu Campus

Position

  • Graduate School of Informatics Department of Core Informatics 

    Professor  2022.04 - Now

  • School of Engineering Department of Information Science 

    Professor  2022.04 - Now

Degree

  • 博士(工学) ( Others )

Research Areas

  • Informatics / Kansei informatics

  • Informatics / Soft computing

Research Interests

  • 遺伝的機械学習

  • 遺伝的アルゴリズム

  • 進化計算

  • 進化型多目的最適化

  • 計算知能工学

  • 知識獲得

  • 対話型計算手法

  • 多目的最適化

  • 並列分散実装

  • ファジィ理論

  • ファジィシステム

  • Genetic Fuzzy Systems

  • Evolutionary Multiobjective Optimization

  • Computational Intelligence

Research subject summary

  • 進化型多目的最適化手法を用いた知識獲得

  • 多目的最適化への進化計算の適用

Research Career

  •  

    計算知能、ファジィシステム、多目的最適化、データマイニング 

Professional Memberships

  • ACM SIGEVO

    2017.04 - Now   Overseas

  • 進化計算学会

    2010.05 - Now

  • 米国電気電子学会(IEEE)

    2000.06 - Now

  • 日本知能情報ファジィ学会

    1999.11 - Now

  • システム制御情報学会

    1998.11 - Now

Awards

  • Best Paper Award

    T. Konishi, N. Masuyama, and Y. Nojima

    2023.08   20th World Congress of the International Fuzzy Systems Association   Effects of complexity enhancements on the search performance of multiobjective fuzzy genetics-based machine learning

  • 進化計算コンペティション2021多目的部門トップ賞

    2021.12   進化計算学会  

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    Country:Japan

  • FAN2021 優秀論文賞

    2021.09   FAN2021実行委員会  

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    Country:Japan

  • 2020 IEEE Transactions on Evolutionary Computation Outstanting Paper Award

    2020.07   IEEE Computational Intelligence Society  

  • Best Presentation Award

    2019.11   20th International Symposium on Advanced Intelligent Systems and 2019 International Conference on Biometrics and Kansei Engineering  

  • FML-based Machine Learning Competition 1st Prize

    2019.07   FUZZ-IEEE2019 and IEEE CEC 2019  

  • Springer Best Paper Award - 1st Prize

    2019.03   10th International Conference on Evolutionary Multi-Criterion Optimization  

  • GECCO Best Paper Award

    2017.07   The Genetic and Evolutionary Computation Conference  

  • TAAI Merit Paper Award

    2015.11   2015 Conference on Technologies and Applications of Artificial Intelligence  

  • ACIIDS2015 Best Regular Paper Award

    2015.03   7th Asian Conference on Intelligent Information and Database Systems  

  • Best Paper Award

    2011.06   2011 IEEE International Conference on Fuzzy Systems  

  • ベストプレゼンテーション賞和田賞

    2010.09   第20回インテリジェントシステムシンポジウム  

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    Country:Japan

  • 奨励賞受賞

    2008.09   日本知能情報ファジィ学会  

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    Country:Japan

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Job Career (off-campus)

  • Osaka Metropolitan University   Department of Core Informatics, Graduate School of Informantics

    2022.04 - Now

  • Osaka Prefecture University   Graduate School of Engineering Division of Electrical Engineering and Information Science

    2020.10 - 2022.03

  • Osaka Prefecture University   Graduate School of Engineering Division of Electrical Engineering and Information Science

    2013.04 - 2020.09

Papers

  • Internally and Generatively Decorrelated Ensemble of First-Order Takagi-Sugeno-Kang Fuzzy Regressors With Quintuply Diversity Guarantee

    E. Zhou, C. -M. Vong, Y. Nojima, and S. Wang

    32 ( 3 )   1288 - 1302   2024.03( ISSN:10636706

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  • Improvement of a Classifier Using Adaptive Resonance Theory-Based Clustering for Multi-Label Mixed Data

    NISHIKAWA Tsuyoshi, MASUYAMA Naoki, NOJIMA Yusuke

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   36 ( 1 )   543 - 549   2024.02( ISSN:13477986 ( eISSN:18817203

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    <p>Various multi-label classifiers have been proposed for multi-label classification problems. Our previous study has proposed an adaptive resonance theory (ART)-based clustering method using correntropy-induced metric (CIM) as a similarity measure, called CIM-based ART for Multi-Label Mixed Data (CA-MLMD). CA-MLMD adaptively and continually generates nodes corresponding to input data, and the generated nodes are used as a classifier. Moreover, CA-MLMD learns new data and label information continually and handles mixed datasets that contain both numerical and categorical attributes. However, CA-MLMD is highly affected by local data points around the node in learning categorical attributes, which may deteriorate classification performance. This study proposes CA-MLMD-weight (CA-MLMD-w), which uses weights defined by categorical attributes of each node and reduces effects of local data points by considering categorical attributes of the entire data. Numerical experiments on real-world datasets show the effectiveness of the proposed method.</p>

    DOI: 10.3156/jsoft.36.1_543

  • Verification of the Effectiveness of Using an Archive Population on Two-Stage Fuzzy Genetics-Based Machine Learning

    KONISHI Takeru, MASUYAMA Naoki, NOJIMA Yusuke

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   36 ( 1 )   565 - 570   2024.02( ISSN:13477986 ( eISSN:18817203

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    <p>Multi-objective fuzzy genetics-based machine learning can efficiently obtain a set of fuzzy classifiers considering the maximization of classification performance and the minimization of the model complexity by using an evolutionary multi-objective optimization method. However, multi-objective fuzzy genetics-based machine learning has a strong bias towards minimizing complexity in the optimization process, making it difficult to generate classifiers with high classification performance. In our previous study, two-stage fuzzy genetics-based machine learning has been proposed to mitigate this bias: first, an accuracy-oriented single-objective optimization is performed, and then a multi-objective optimization is performed to maximize the classification performance and minimize the complexity. The use of an archive population has also been proposed to obtain a better set of classifiers in two-stage fuzzy genetics-based machine learning. However, the effects of the use of an archive population on a set of classifiers obtained by two-stage fuzzy genetics-based machine learning have not been fully investigated. In this paper, we investigate the effects through computational experiments on a wide variety of real-world datasets.</p>

    DOI: 10.3156/jsoft.36.1_565

  • CNN-LSTM for Heartbeat Sound Classification

    Aji N.B.

    International Journal on Informatics Visualization   8 ( 2 )   735 - 741   2024

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  • Hybrid-ensemble-based interpretable TSK fuzzy classifier for imbalanced data

    Z. Bian, J. Zhang, Y. Nojima, F.-l. Chung, and S. Wang

    98   2023.10( ISSN:15662535

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  • A Decomposition-based Multi-modal Multi-objective Evolutionary Algorithm with Problem Transformation into Two-objective Subproblems

    Y. Nojima, Y. Fujii, N. Masuyama, Y. Liu, and H. Ishibuchi

    399 - 402   2023.07( ISBN:9798400701207

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  • System design optimization with mixed subsystems failure dependencies. Reviewed International coauthorship

    M. A. Mellal, E. Zio, S. Al-Dahidi, N. Masuyama, and Y. Nojima

    Reliab. Eng. Syst. Saf.   231   109005 - 109005   2023.03( ISSN:09518320

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    Publishing type:Research paper (scientific journal)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1016/j.ress.2022.109005

  • Analytical Methods to Separately Evaluate Convergence and Diversity for Multi-objective Optimization. Reviewed International coauthorship

    T. Kinoshita, N. Masuyama, Y. Nojima, and H. Ishibuchi,

    MIC   13838 LNCS   172 - 186   2023( ISSN:03029743 ( ISBN:9783031265037

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1007/978-3-031-26504-4_13

    Other URL: https://dblp.uni-trier.de/db/conf/metaheuristics/metaheuristics2022.html#KinoshitaMNI22

  • Report on Open Space Discussion 2022

    Nakata Masaya, Uchitane Takeshi, Kushida Junichi, Tanaka Shoichiro, Tanigaki Yuki, Nishihara Kei, Harada Tomohiro, Nojima Yusuke

    Transaction of the Japanese Society for Evolutionary Computation   14 ( 1 )   12 - 17   2023( eISSN:21857385

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    <p>On December 16, 2022, Open Space Discussion 2022 (OSD2022) was held as a pre-event of the 2022 Symposium on Evolutionary Computation. This event was motivated to provide an opportunity to share, discuss, and create future directions in evolutionary computation. This paper provides an event report for OSD2022, including a summary of the discussions made as well as participant feedback.</p>

    DOI: 10.11394/tjpnsec.14.12

  • Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-Based Clustering for Many-Objective Optimization

    T. Kinoshita, N. Masuyama, Y. Liu, Y. Nojima, and H. Ishibuchi

    11   126066 - 126086   2023

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  • Knowledge Graph-Based Genetic Fuzzy Agent for Human Intelligence and Machine Co-Learning

    Chang-Shing Lee, Mei-Hui Wang, Chih-Yu Chen, Marek Reformat, Yusuke Nojima, Naoyuki Kubota

    2023 ( ISSN:10987584 ( ISBN:9798350332285

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  • Fuzzy Classifiers with a Two-Stage Reject Option

    Y. Nojima, K. Kawano, H. Shimahara, E. Vernon, N. Masuyama, and H. Ishibuchi

    2023 ( ISSN:10987584 ( ISBN:9798350332285

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  • Composition-Designed Multielement Perovskite Oxides for Oxygen Evolution Catalysis Reviewed

    Yuichi Okazaki, Yushi Fujita, Hidenobu Murata, Naoki Masuyama, Yusuke Nojima, Hidekazu Ikeno, Shunsuke Yagi, Ikuya Yamada

    Chemistry of Materials   34 ( 24 )   10973 - 10981   2022.12( ISSN:08974756 ( eISSN:1520-5002

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    Publishing type:Research paper (scientific journal)   Kind of work:Joint Work   International / domestic magazine:International journal  

    Oxygen evolution reaction (OER) catalysts play an essential role in energy-conversion electrochemical reactions. High-entropy oxides (HEOs) were recently investigated as promising candidates to realize highly active and cost-effective OER catalysts. Since the vast composition space for the HEOs needs considerable efforts to find promising catalysts, the further development beyond simple chemical compositions like equimolar ones has not been achieved yet. In this study, we conducted the fast and efficient design of the perovskite of La(Cr, Mn, Fe, Co, Ni)O3 with high OER catalytic activity using Bayesian optimization and found the relationship between chemical compositions and OER catalytic activities. The multielement perovskites with the optimized compositions exhibited much higher activities than the equimolar LaCr1/5Mn1/5Fe1/5Co1/5Ni1/5O3, which was previously reported as an active catalyst. Bayesian optimization adjusted the concentrations of OER active elements of Fe, Co, and Ni in high contents to enhance the catalytic activities. The optimization also indicates that the OER inactive elements (Cr and Mn) in perovskites even promote the OER activities. These findings suggest the solution of data-based predictions to improve catalytic performances in multielement transition-metal oxides.

    DOI: 10.1021/acs.chemmater.2c02986

  • Error-reject tradeoff analysis on two-stage classifier design with a reject option Reviewed

    E. M. Vernon, N. Masuyama, and Y. Nojima

    Proc. of World Automation Congress (WAC 2022)   2022.10

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    Kind of work:Joint Work  

  • Behavior analysis of constrained multiobjective evolutionary algorithms using scalable constrained multi-modal distance minimization problems Reviewed

    M. Yano, N. Masuyama, and Y. Nojim

    Proc. of World Automation Congress (WAC 2022)   2022.10

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    Kind of work:Joint Work  

  • A Multi-Population Multi-Objective Evolutionary Algorithm Based on the Contribution of Decision Variables to Objectives for Large-Scale Multi/Many-Objective Optimization.

    Xu Y, Xu C, Zhang H, Huang L, Liu Y, Nojima Y, Zeng X

    IEEE Transactions on Cybernetics   PP   2022.06( ISSN:2168-2267

  • Prediction by fuzzy clustering and KNN on validation data with parallel ensemble of interpretable TSK fuzzy classifiers Reviewed International coauthorship

    X. Zhang, Y. Nojima, H. Ishibuchi, W. Hu, and S. Wang

    52 ( 1 )   400 - 414   2022.01

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    Kind of work:Joint Work  

  • Adaptive Resonance Theory-Based Topological Clustering With a Divisive Hierarchical Structure Capable of Continual Learning.

    N. Masuyama, N. Amako, Y. Yamada, Y. Nojima, and H. Ishibuchi

    IEEE Access   10   68042 - 68056   2022

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/ACCESS.2022.3186479

  • Search Process Analysis of Multiobjective Evolutionary Algorithms using Convergence-Diversity Diagram. Reviewed International coauthorship

    T. Kinoshita, N. Masuyama, and Y. Nojima

    SCIS/ISIS   1 - 6   2022( ISBN:9781665499248

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SCISISIS55246.2022.10001961

    Other URL: https://dblp.uni-trier.de/db/conf/scisisis/scisisis2022.html#KinoshitaMN22

  • Multi-Label Classification via Adaptive Resonance Theory-Based Clustering Reviewed International coauthorship

    N. Masuyama, Y. Nojima, C. K. Loo, and H. Ishibuchi

    IEEE Transactions on Pattern Analysis and Machine Intelligence   45 ( 7 )   8696 - 8712   2022( ISSN:01628828

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    Publishing type:Research paper (scientific journal)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/TPAMI.2022.3230414

  • Evolutionary Multi-Objective Multi-Tasking for Fuzzy Genetics-Based Machine Learning in Multi-Label Classification. Reviewed International coauthorship

    Y. Omozaki, N. Masuyama, Y. Nojima, and H. Ishibuchi

    FUZZ-IEEE   2022-July   1 - 8   2022( ISSN:10987584 ( ISBN:9781665467100

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/FUZZ-IEEE55066.2022.9882681

    Other URL: https://dblp.uni-trier.de/db/conf/fuzzIEEE/fuzzIEEE2022.html#OmozakiMNI22

  • Effects of Accuracy-based Single-Objective Optimization in Multiobjective Fuzzy Genetics-based Machine Learning. Reviewed

    T. Kinoshita, N. Masuyama, and Y. Nojima

    SCIS/ISIS   1 - 6   2022( ISBN:9781665499248

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SCISISIS55246.2022.10002139

    Other URL: https://dblp.uni-trier.de/db/conf/scisisis/scisisis2022.html#KonishiMN22

  • Adaptive Resonance Theory-based Clustering for Handling Mixed Data. Reviewed International coauthorship

    N. Masuyama, Y. Nojima, H. Ishibuchi, and Z. Liu

    IJCNN   2022-July   1 - 8   2022( ISBN:9781728186719

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/IJCNN55064.2022.9892060

    Other URL: https://dblp.uni-trier.de/db/conf/ijcnn/ijcnn2022.html#MasuyamaNIL22

  • A Fully Interpretable First-order TSK Fuzzy System and Its Training with Negative Entropic and Rule-stability-based Regularization Reviewed International coauthorship

    E. Zhou, C. M. Vong, Y. Nojima, and S. Wang

    IEEE Transactions on Fuzzy Systems   31 ( 7 )   2305 - 2319   2022( ISSN:10636706

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    Publishing type:Research paper (scientific journal)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/TFUZZ.2022.3223700

  • Report on Open Space Discussion 2021 Reviewed

    Nojima Yusuke, Takagi Hideyuki, Munetomo Masaharu, Hamada Naoki, Nishihara Kei, Takadama Keiki, Sato Hiroyuki, Kiribuchi Daiki, Miyakawa Minami

    Transaction of the Japanese Society for Evolutionary Computation   13 ( 1 )   1 - 9   2022( eISSN:21857385

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    <p>This paper is a report on Open Space Discussion (OSD) held in Evolutionary Computation Symposium 2021. The purpose of OSD is to share and discuss problems at hand and future research targets related to evolutionary computation. Discussion topics are voluntarily proposed by some of the participants, and other participants freely choose one to join in the discussion. Through free discussions based on the open space technology framework, it is expected that participants will have new research ideas and start some collaborations. This paper gives the concept of OSD and introduces six topics discussed this year. This paper also shows the responses to the questionnaire on OSD for future discussions, collaborations, and related events.</p>

    DOI: 10.11394/tjpnsec.13.1

  • Validation data accuracy as an additional objective in multiobjective fuzzy genetics-based machine learning Reviewed

    S. A. F. Dilone, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of The 22th International Symposium on Advanced Intelligent Systems 雑誌   2021.12

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    Kind of work:Joint Work  

  • ゲーム内イベントに対する認知的バイアスを考慮した乱数生成問題 - 進化計算コンペティション2020の結果報告 Reviewed

    濱田直希,於保俊,谷垣勇輝,原田智広,能島裕介

    進化計算学会論文誌 雑誌   12 ( 3 )   112 - 124   2021.12

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    Kind of work:Joint Work  

  • Effects of different optimization formulations in evolutionary reinforcement learning on diverse behavior generation Reviewed

    V. Villin, N. Masuyama, and Y. Nojima

    Proc. of 2021 IEEE Symposium Series on Computational Intelligence 雑誌   2021.12

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    Kind of work:Joint Work  

  • Hierarchical topological clustering with automatic parameter estimation Reviewed

    Y. Yamada, N. Amako, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of The 22th International Symposium on Advanced Intelligent Systems 雑誌   2021.12

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    Kind of work:Joint Work  

  • Realizing deep high-order TSK fuzzy classifier by ensembling interpretable zero-order TSK fuzzy subclassifiers Reviewed

    B. Qin, Y. Nojima, H. Ishibuchi, and S. Wang

    IEEE Trans. on Fuzzy Systems 雑誌   29 ( 11 )   3441 - 3455   2021.11

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    Kind of work:Joint Work  

  • Multi-modal multi-objective traveling salesman problem and its evolutionary optimizer Reviewed

    Y. Liu, L. Xu, Y. Han, N. Masuyama, Y. Nojima, H. Ishibuchi, and G. G. Yen

    Proc. of 2021 IEEE International Conference on Systems, Man, and Cybernetics 雑誌   2021.10

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    Kind of work:Joint Work  

  • Distributed flow shop scheduling with sequence-dependent setup times using an improved iterated greedy algorithm Reviewed

    X. Han, Y. Han, Q. Chen, J. Li, H. Sang, Y. Liu, Q. Pan, and Y. Nojima

    Complex System Modeling and Simulation 雑誌   1 ( 3 )   198 - 217   2021.09

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    Kind of work:Joint Work  

  • Fuzzy style k-plane clustering Reviewed

    G. Suhang, Y. Nojima, H. Ishibuchi, and S. Wang

    IEEE Trans. on Fuzzy Systems 雑誌   29 ( 6 )   1518 - 1532   2021.06

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    Kind of work:Joint Work  

  • クラス別FTCAに基づく識別器設計 Reviewed

    増山直輝, 坪田一希, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   33 ( 1 )   543 - 548   2021.02

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    Kind of work:Joint Work  

  • クラス不均衡データに対するミシガン型ファジィ遺伝的機械学習 Reviewed

    西原光洋, 増山直輝, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   33 ( 1 )   525 - 530   2021.02

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    Kind of work:Joint Work  

  • マルチラベル多目的ファジィ遺伝的機械学習の多数目的最適化への拡張 Reviewed

    面崎祐一, 増山直輝, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   33 ( 1 )   531 - 536   2021.02

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    Kind of work:Joint Work  

  • 2目的問題に変換する分解ベース進化型マルチモーダル多目的最適化アルゴリズム Reviewed

    藤井祐人, 増山直輝, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   33 ( 1 )   537 - 542   2021.02

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    Kind of work:Joint Work  

  • Random Number Generation Problems based on Cognitive Biases for In-Game Events Reviewed

    Naoki Hamada, Oho Suguru, Tanigaki Yuki, Harada Tomohiro, Nojima Yusuke

    Transaction of the Japanese Society for Evolutionary Computation   12 ( 3 )   112 - 124   2021( eISSN:21857385

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    Publishing type:Research paper (scientific journal)   Kind of work:Joint Work   International / domestic magazine:Domestic journal  

    <p>The Evolutionary Computation Competition (EC-Comp) is an optimization competition launched in 2017 to promote real-world applications of evolutionary computation and interaction between industry and academia. For 2017—2019, the competition has focused on continuous optimization problems in the manufacturing and aerospace industries. With the aim of exploring new areas of applications, EC-Comp2020 focused on "Designing Random Numbers to Entertain Game Players" in the game industry. Random numbers used in video games are usually generated by general-purpose pseudo random number generators, such as Mersenne Twister and Xorshift. However, these mathematically unbiased random numbers often make game players feel biased (sometimes even deliberately chosen), causing strong frustration. It is known that humans have various biases toward probabilistic events, and unbiased random numbers seem rather biased to game players. This competition asked to design a random number sequence that makes game players feel unbiased (but actually biased). This paper describes the definition of the random number design problem for entertaining game players in EC-Comp2020. This paper also explains the participants' optimization methods, accompanied with brief analysis on their results. </p>

    DOI: 10.11394/tjpnsec.12.112

    CiNii Article

  • Fuzzy Style K-Plane Clustering.

    Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang 0001

    IEEE Trans. Fuzzy Syst.   29 ( 6 )   1518 - 1532   2021

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TFUZZ.2020.2979676

  • Multi-Modal Multi-Objective Traveling Salesman Problem and its Evolutionary Optimizer.

    Yiping Liu, Liting Xu, Yuyan Han, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi, Gary G. Yen

    SMC   770 - 777   2021( ISBN:9781665442077

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    Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/SMC52423.2021.9658818

    Other URL: https://dblp.uni-trier.de/db/conf/smc/smc2021.html#LiuXHMNIY21

  • Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation.

    Victor Villin, Naoki Masuyama, Yusuke Nojima

    SSCI   1 - 8   2021( ISBN:9781728190488

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    Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/SSCI50451.2021.9659949

    Other URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2021.html#VillinMN21

  • Multi-label classification based on adaptive resonance theory Reviewed

    N. Masuyama, Y. Nojima, C. K. Loo, and H. Ishibuchi

    Proc. of 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020)   1 - 8   2020.12

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    Kind of work:Joint Work  

  • Divisive hierarchical clustering based on adaptive resonance theory Reviewed

    Y. Yamada, N. Masuyama, N. Amako, Y. Nojima, C. K. Loo, and H. Ishibuchi

    Proc. of 2020 International Symposium on Community-centric Systems (CcS 2020)   1 - 8   2020.09

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    Kind of work:Joint Work  

  • A hybrid two-stage financial stock forecasting algorithm based on clustering and ensemble learning Reviewed

    Y. Xu, C. Yang, S. Peng and Y. Nojima

    Applied Intelligence 雑誌   50 ( 11 )   3852 - 2867   2020.07

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    Kind of work:Joint Work  

  • Multilayer clustering based on adaptive resonance theory for noisy environments Reviewed

    N. Amako, N. Masuyama, C. K. Loo, Y. Nojima, Y. Liu, and H. Ishibuchi

    Proc. of 2020 International Joint Conference on Neural Networks (IJCNN 2020)   1 - 8   2020.07

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    Kind of work:Joint Work  

  • Effects of local mating in inter-task crossover on the performance of decomposition-based evolutionary multiobjective multitask optimization algorithms Reviewed

    R. Hashimoto, T. Urita, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2020 IEEE Congress on Evolutionary Computation (CEC 2020)   1 - 8   2020.07

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    Kind of work:Joint Work  

  • On the normalization in evolutionary multi-modal multi-objective optimization Reviewed

    Y. Liu, H. Ishibuchi, G. G. Yen, Y. Nojima, N. Masuyama, and Y. Han

    Proc. of 2020 IEEE Congress on Evolutionary Computation (CEC 2020)   1 - 8   2020.07

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    Kind of work:Joint Work  

  • Multiobjective fuzzy genetics-based machine learning for multi-label classification Reviewed

    Y. Omozaki, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020)   1 - 8   2020.07

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    Kind of work:Joint Work  

  • Towards realistic optimization benchmarks: A questionnaire on the properties of real-world problems Reviewed

    K. v. d. Blom, T. M. Deist, T. Tusar, M. Marchi, Y. Nojima, A. Oyama, V. Volz, and B. Naujoks

    Proc of 2020 Genetic and Evolutionary Computation Conference Companion   2020.07

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    Kind of work:Joint Work  

  • Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms Reviewed

    H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima

    Proc. of 2020 Genetic and Evolutionary Computation Conference   507 - 515   2020.07

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    Kind of work:Joint Work  

  • Adapting reference vectors and scalarizing functions by growing neural gas to handle irregular Pareto fronts Reviewed

    Y. Liu, H. Ishibuchi, N. Masuyama, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌   24 ( 3 )   439 - 453   2020.06

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  • Many-objective problems are not always difficult for Pareto dominance-based evolutionary algorithms Reviewed

    H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima

    Proc. of 24th European Conference on Artificial Intelligence (ECAI 2020)   291 - 298   2020.06

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  • Cluster-based membership function acquisition approaches for mining fuzzy temporal association rules Reviewed

    C.-H. Chen, H. Chou, T.-P. Hong, and Y. Nojima

    IEEE Access 雑誌   8   123996 - 124006   2020.06

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  • Handling imbalance between convergence and diversity in the decision space in evolutionary multi-modal multi-objective optimization Reviewed

    Y. Liu, H. Ishibuchi, G. G. Yen, Y. Nojima, and N. Masuyama

    IEEE Trans. on Evolutionary Computation 雑誌   24 ( 3 )   551 - 565   2020.06

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  • A novel classification method from the perspective of fuzzy social networks based on physical and implicit style features of data Reviewed

    G. Suhang, Y. Nojima, H. Ishibuchi, and S. Wang

    IEEE Trans. on Fuzzy Systems 雑誌   28 ( 2 )   361 - 375   2020.02

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  • 進化型多目的マルチタスク最適化手法におけるタスク間交叉時の親個体が探索性能に与える影響 Reviewed

    橋本龍一, 増山直輝, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   32 ( 1 )   501 - 506   2020.02

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  • 未知クラスの継続的な学習を可能とするファジィ遺伝的機械学習手法 Reviewed

    入江勇斗, 増山直輝, 能島裕介, 石渕久生

    日本知能情報ファジィ学会誌 雑誌   32 ( 1 )   512 - 517   2020.02

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  • Towards realistic optimization benchmarks: a questionnaire on the properties of real-world problems.

    Koen van der Blom, Timo M. Deist, Tea Tusar, Mariapia Marchi, Yusuke Nojima, Akira Oyama, Vanessa Volz, Boris Naujoks

    GECCO '20: Genetic and Evolutionary Computation Conference   293 - 294   2020

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    Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/3377929.3389974

    Other URL: https://dblp.uni-trier.de/db/conf/gecco/gecco2020c.html#BlomDTMNOVN20

  • On the Normalization in Evolutionary Multi-Modal Multi-Objective Optimization. Reviewed International coauthorship

    Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama, Yuyan Han

    IEEE Congress on Evolutionary Computation(CEC)   1 - 8   2020( ISBN:9781728169293

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC48606.2020.9185899

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2020.html#LiuIYNMH20

  • Multiobjective Fuzzy Genetics-Based Machine Learning for Multi-Label Classification. Reviewed International coauthorship

    Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi

    29th IEEE International Conference on Fuzzy Systems(FUZZ-IEEE)   1 - 8   2020( ISBN:9781728169323

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/FUZZ48607.2020.9177804

    Other URL: https://dblp.uni-trier.de/db/conf/fuzzIEEE/fuzzIEEE2020.html#OmozakiMNI20

  • Effects of Local Mating in Inter-task Crossover on the Performance of Decomposition-based Evolutionary Multiobjective Multitask optimization Algorithms. Reviewed International coauthorship

    Ryuichi Hashimoto, Toshiki Urita, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi

    IEEE Congress on Evolutionary Computation(CEC)   1 - 8   2020( ISBN:9781728169293

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC48606.2020.9185871

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2020.html#HashimotoUMNI20

  • Fuzzy sets for decision making in emerging domains.

    Irene Díaz, Yusuke Nojima

    Fuzzy Sets Syst.   395   197 - 198   2020

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    DOI: 10.1016/j.fss.2020.05.005

  • Handling Imbalance Between Convergence and Diversity in the Decision Space in Evolutionary Multimodal Multiobjective Optimization.

    Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama

    IEEE Trans. Evol. Comput.   24 ( 3 )   551 - 565   2020

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TEVC.2019.2938557

  • Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms. Reviewed International coauthorship

    Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima

    ECAI 2020 - 24th European Conference on Artificial Intelligence(ECAI)   291 - 298   2020( ISBN:9781643681009

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.3233/FAIA200105

    Other URL: https://dblp.uni-trier.de/db/conf/ecai/ecai2020.html#IshibuchiMMN20

  • Multi-label Classification Based on Adaptive Resonance Theory. Reviewed International coauthorship

    Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi

    2020 IEEE Symposium Series on Computational Intelligence(SSCI)   1913 - 1920   2020( ISBN:9781728125473

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SSCI47803.2020.9308356

    Other URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2020.html#MasuyamaNLI20

  • Multilayer Clustering Based on Adaptive Resonance Theory for Noisy Environments. Reviewed International coauthorship

    Narito Amako, Naoki Masuyama, Chu Kiong Loo, Yusuke Nojima, Yiping Liu, Hisao Ishibuchi

    2020 International Joint Conference on Neural Networks(IJCNN)   1 - 8   2020( ISBN:9781728169262

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/IJCNN48605.2020.9207071

    Other URL: https://dblp.uni-trier.de/db/conf/ijcnn/ijcnn2020.html#AmakoMLNLI20

  • Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms. Reviewed International coauthorship

    Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima

    GECCO '20: Genetic and Evolutionary Computation Conference(GECCO)   507 - 515   2020( ISBN:9781450371285

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1145/3377930.3390166

    Other URL: https://dblp.uni-trier.de/db/conf/gecco/gecco2020.html#IshibuchiMMN20

  • Divisive Hierarchical Clustering Based on Adaptive Resonance Theory. Reviewed International coauthorship

    Yuna Yamada, Naoki Masuyama, Narito Amako, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi

    International Symposium on Community-centric Systems(CcS)   1 - 6   2020( ISBN:9781728187419

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CcS49175.2020.9231474

    Other URL: https://dblp.uni-trier.de/db/conf/ccs3/ccs2020.html#YamadaMANLI20

  • Cluster-Based Membership Function Acquisition Approaches for Mining Fuzzy Temporal Association Rules.

    Chun-Hao Chen, Hsiang Chou, Tzung-Pei Hong, Yusuke Nojima

    IEEE Access   8   123996 - 124006   2020

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/ACCESS.2020.3004095

  • Adapting Reference Vectors and Scalarizing Functions by Growing Neural Gas to Handle Irregular Pareto Fronts.

    Yiping Liu, Hisao Ishibuchi, Naoki Masuyama, Yusuke Nojima

    IEEE Trans. Evol. Comput.   24 ( 3 )   439 - 453   2020

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TEVC.2019.2926151

  • A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data.

    Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang 0001

    IEEE Trans. Fuzzy Syst.   28 ( 2 )   361 - 375   2020

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TFUZZ.2019.2906855

  • A hybrid two-stage financial stock forecasting algorithm based on clustering and ensemble learning.

    Ying Xu, Cuijuan Yang, Shaoliang Peng, Yusuke Nojima

    Appl. Intell.   50 ( 11 )   3852 - 3867   2020

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    DOI: 10.1007/s10489-020-01766-5

  • Development of a GUI tool for FML-based fuzzy system modeling Reviewed

    Y. Omozaki, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 20th International Symposium on Advanced Intelligent Systems and 2019 International Conference on Biometrics and Kansei Engineering   116 - 121   2019.12

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  • Optimal distributions of solutions for hypervolume maximization on triangular and inverted triangular Pareto fronts of four-objective Problems Reviewed

    H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima

    Proc. of 2019 IEEE Symposium Series on Computational Intelligence   1857 - 1864   2019.12

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  • Fast topological adaptive resonance theory based on correntropy induced metric Reviewed

    N. Masuyama, C.-K. Loo, H. Ishibuchi, N. Amako, Y. Nojima, and Y. Liu

    Proc. of 2019 IEEE Symposium Series on Computational Intelligence   2215 - 2221   2019.12

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  • Effect of solution information sharing between tasks on the search ability of evolutionary multiobjective multitasking algorithms Reviewed

    R. Hashimoto, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2019 IEEE Symposium Series on Computational Intelligence   2681 - 2688   2019.12

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  • Dots-type constrained multiobjective distance minimization problems Reviewed

    T. Fukase, N. Masuyama, Y. Nojima, Y. Liu, and H. Ishibuchi

    Proc. of 20th International Symposium on Advanced Intelligent Systems and 2019 International Conference on Biometrics and Kansei Engineering   55 - 56   2019.12

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  • Constrained multiobjective distance minimization problems Reviewed

    Y. Nojima, T. Fukase, Y. Liu, N. Masuyama, and H. Ishibuchi

    Proc. of 2019 Genetic and Evolutionary Computation Conference   586 - 594   2019.07

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  • A GFML-based robot agent for human and machine cooperative learning on game of Go Reviewed

    C.-S. Lee, M.-H. Wang, L.-C. Chen, Y. Nojima, T.-X. Huang, J. Woo, N. Kubota, E. Sato-Shimokawara, and T. Yamaguchi

    Proc. of 2019 IEEE Congress on Evolutionary Computation   770 - 776   2019.06

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  • Two-layered weight vector specification in decomposition-based multi-objective algorithms for many-objective optimization problems Reviewed

    H. Ishibuchi, R. Imada, N. Masuyama, and Y. Nojima

    Proc. of 2019 IEEE Congress on Evolutionary Computation   2435 - 2442   2019.06

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  • A multiobjective test suite with hexagon Pareto fronts and various feasible regions Reviewed

    T. Matsumoto, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2019 IEEE Congress on Evolutionary Computation   2059 - 2066   2019.06

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  • Searching for local Pareto optimal solutions: A case study on polygon-based problems Reviewed

    Y. Liu, H. Ishibuchi, Y. Nojima, N. Masuyama, and Y. Han

    Proc. of 2019 IEEE Congress on Evolutionary Computation   873 - 880   2019.06

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  • Comparison of hypervolume, IGD and IGD+ from the viewpoint of optimal distributions of solutions Reviewed

    H. Ishibuchi, R. Imada, N. Masuyama, and Y. Nojima

    Proc. of 10th International Conference on Evolutionary Multi-Criterion Optimization 雑誌   332 - 345   2019.03

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  • Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems. Reviewed International coauthorship

    Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima

    IEEE Congress on Evolutionary Computation(CEC)   2434 - 2441   2019( ISBN:9781728121536

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC.2019.8790344

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2019.html#IshibuchiIMN19

  • Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning.

    Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota, Yusuke Nojima, Yiping Liu

    IEEE Access   7   76920 - 76936   2019

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/ACCESS.2019.2921832

  • Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems. Reviewed International coauthorship

    Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Yuyan Han

    IEEE Congress on Evolutionary Computation(CEC)   896 - 903   2019( ISBN:9781728121536

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC.2019.8790066

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2019.html#LiuINMH19

  • Optimal Distributions of Solutions for Hypervolume Maximization on Triangular and Inverted Triangular Pareto Fronts of Four-Objective Problems. Reviewed International coauthorship

    Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima

    IEEE Symposium Series on Computational Intelligence(SSCI)   1857 - 1864   2019( ISBN:9781728124858

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SSCI44817.2019.9003032

    Other URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2019.html#IshibuchiMMN19

  • Fast Topological Adaptive Resonance Theory Based on Correntropy Induced Metric. Reviewed International coauthorship

    Naoki Masuyama, Narito Amako, Yusuke Nojima, Yiping Liu, Chu Kiong Loo, Hisao Ishibuchi

    IEEE Symposium Series on Computational Intelligence(SSCI)   2215 - 2221   2019( ISBN:9781728124858

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SSCI44817.2019.9003098

    Other URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2019.html#MasuyamaANLLI19

  • Guest Editorial: Special Issue on New Advances in Deep-Transfer Learning.

    Zhaohong Deng, Jie Lu 0001, Dongrui Wu, Kup-Sze Choi, Shiliang Sun, Yusuke Nojima

    IEEE Trans. Emerg. Top. Comput. Intell.   3 ( 5 )   357 - 359   2019

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TETCI.2019.2936641

  • A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go. Reviewed International coauthorship

    Chang-Shing Lee, Mei-Hui Wang, Li-Chuang Chen, Yusuke Nojima, Tzong-Xiang Huang, Jinseok Woo, Naoyuki Kubota, Eri Sato-Shimokawara, Toru Yamaguchi

    IEEE Congress on Evolutionary Computation(CEC)   793 - 799   2019( ISBN:9781728121536

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC.2019.8790015

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2019.html#LeeWCNHWKSY19

  • Effect of Solution Information Sharing between Tasks on the Search Ability of Evolutionary Multiobjective Multitasking Algorithms. Reviewed International coauthorship

    Ryuichi Hashimoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi

    IEEE Symposium Series on Computational Intelligence(SSCI)   2671 - 2678   2019( ISBN:9781728124858

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/SSCI44817.2019.9002984

    Other URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2019.html#HashimotoMNI19

  • Constrained multiobjective distance minimization problems. Reviewed International coauthorship

    Yusuke Nojima, Takafumi Fukase, Yiping Liu, Naoki Masuyama, Hisao Ishibuchi

    Proceedings of the Genetic and Evolutionary Computation Conference(GECCO)   586 - 594   2019( ISBN:9781450361118

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1145/3321707.3321878

    Other URL: https://dblp.uni-trier.de/db/conf/gecco/gecco2019.html#NojimaFLMI19

  • Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions. Reviewed International coauthorship

    Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima

    Evolutionary Multi-Criterion Optimization - 10th International Conference(EMO)   332 - 345   2019( ISBN:9783030125974

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1007/978-3-030-12598-1_27

    Other URL: https://dblp.uni-trier.de/db/conf/emo/emo2019.html#IshibuchiIMN19

  • A Multiobjective Test Suite with Hexagon Pareto Fronts and Various Feasible Regions. Reviewed International coauthorship

    Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi

    IEEE Congress on Evolutionary Computation(CEC)   2058 - 2065   2019( ISBN:9781728121536

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    Publishing type:Research paper (international conference proceedings)   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1109/CEC.2019.8790277

    Other URL: https://dblp.uni-trier.de/db/conf/cec/cec2019.html#MatsumotoMNI19

  • A preliminary study of Michigan-style fuzzy genetics-based machine learning for class incremental problems Reviewed

    Y. Irie, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems 雑誌   713 - 717   2018.12

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  • Effect of the number of constraints on the performance of multi-objective evolutionary algorithms Reviewed

    Y. Tanigaki, N. Masuyama, and Y. Nojima

    International Journal of Computer Science and Network Security 雑誌   18 ( 12 )   221 - 231   2018.12

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    Kind of work:Joint Work  

  • Reference point specification in inverted generational distance for triangular linear Pareto front Reviewed

    H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌   22 ( 6 )   961 - 975   2018.12

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  • Multiobjective evolutionary data mining for performance improvement of evolutionary multiobjective optimization Reviewed

    Y. Nojima, Y. Tanigaki, N. Masuyama, and H. Ishibuchi

    Proc. of 2018 IEEE International Conference on Systems, Man, and Cybernetics 雑誌   741 - 746   2018.10

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  • Performance comparison of multiobjective evolutionary algorithms on problems with partially different properties from popular scalable test suites Reviewed

    T. Matsumoto, N. Masuyama, Y. Nojima, and H. Ishibuchi

    Proc. of 2018 IEEE International Conference on Systems, Man, and Cybernetics 雑誌   765 - 770   2018.10

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  • A double-niched evolutionary algorithm and its behaviors on polygon-based problems Reviewed

    Y. Liu, H. Ishibuchi, Y. Nojima, N. Masuyama, and K. Shang

    Proc. of 15th International Conference on Parallel Problem Solving from Nature 雑誌   262 - 273   2018.09

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    Kind of work:Joint Work  

  • Use of two reference points in hypervolume-based evolutionary multiobjective optimization algorithms Reviewed

    H. Ishibuchi, R. Imada, N. Masuyama, and Y. Nojima

    Proc. of 15th International Conference on Parallel Problem Solving from Nature 雑誌   384 - 396   2018.09

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  • Improving 1by1EA to handle various shapes of Pareto fronts Reviewed

    Y. Liu, H. Ishibuchi, Y. Nojima, N. Masuyama, and K. Shang

    Proc. of 15th International Conference on Parallel Problem Solving from Nature 雑誌   311 - 322   2018.09

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    Kind of work:Joint Work  

  • How to specify a reference point in hypervolume calculation for fair performance comparison Reviewed

    H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima

    Evolutionary Computation 雑誌   26 ( 3 )   411 - 440   2018.08

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  • Analysis of evolutionary multi-tasking as an island model Reviewed

    R. Hashimoto, H. Ishibuchi, N. Masuyama, and Y. Nojima

    Companion of 2018 Genetic and Evolutionary Computation Conference 雑誌   1894 - 1897   2018.07

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    Kind of work:Joint Work  

  • Dynamic specification of a reference point for hypervolume calculation in SMS-EMOA Reviewed

    H. Ishibuchi, R. Imada, N. Masuyama, and Y. Nojima

    Proc. of 2018 IEEE Congress on Evolutionary Computation 雑誌   701 - 708   2018.07

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  • Dual-grid model of MOEA/D for evolutionary constrained multiobjective optimization Reviewed

    H. Ishibuchi, T. Fukase, N. Masuyama, and Y. Nojima

    Proc. of 2018 Genetic and Evolutionary Computation Conference 雑誌   665 - 672   2018.07

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  • Topological kernel Bayesian ARTMAP Reviewed

    N. Masuyama, C. K. Loo, H. Ishibuchi, Y. Nojima, and Y. Liu

    Proc. of World Automation Congress 雑誌   316 - 321   2018.06

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  • Topological clustering via adaptive resonance theory with information theoretic learning Reviewed

    N. Masuyama, C. K. Loo, H. Ishibuchi, N. Kubota, Y. Nojima, and Y. Liu

    IEEE Access 雑誌   7   76920 - 76936   2018.06

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  • A framework for large-scale multi-objective optimization based on problem transformation Reviewed

    H. Zille, H. Ishibuchi, S. Mostaghim, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌   22 ( 2 )   260 - 274   2018.04

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  • On the effect of normalization in MOEA/D for multi-objective and many-objective optimization Reviewed

    H. Ishibuchi, K. Doi, and Y. Nojima

    Complex & Intelligent Systems 雑誌   3   2017.12

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    Kind of work:Joint Work  

  • Use of inverted triangular weight vectors in decomposition-based many-objective algorithms Reviewed

    K. Doi, R. Imada, Y. Nojima, and H. Ishibuchi

    Proc. of 11th International Conference on Simulated Evolution and Learning 雑誌   321 - 333   2017.11

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  • Use of inverted triangular weight vectors in decomposition-based multiobjective algorithms Reviewed

    H. Ishibuchi, R. Imada, K. Doi, and Y. Nojima

    Proc. of 2017 IEEE International Conference on Systems, Man, and Cybernetics 雑誌   373 - 378   2017.10

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  • Multi-objective GAssist with NSGA-II Reviewed

    H. Gao, Y. Nojima, and H. Ishibuchi

    Proc. of 18th International Symposium on Advanced Intelligent Systems 雑誌   696 - 703   2017.10

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  • Multiobjective fuzzy genetics-based machine learning based on MOEA/D with its modifications Reviewed

    Y. Nojima, K. Arahari, S. Takemura, and H. Ishibuchi

    Proc. of 2017 IEEE International Conference on Fuzzy Systems 雑誌   2017.07

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  • Reference point specification in hypervolume calculation for fair comparison and efficient search Reviewed

    H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima

    Proc. of 2017 Genetic and Evolutionary Computation Conference 雑誌   585 - 592   2017.07

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    Kind of work:Joint Work  

  • Multiobjective data mining from solutions by evolutionary multiobjective optimization Reviewed

    Y. Nojima, Y. Tanigaki, and H. Ishibuchi

    Proc. of 2017 Genetic and Evolutionary Computation Conference   617 - 624   2017.07

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  • Evolutionary fuzzy rule-based methods for monotonic classification Reviewed

    J. Alcala-Fdez, R. Alcala, S. Gonzalez, Y. Nojima, and S. Garcia

    IEEE Trans. on Fuzzy Systems 雑誌   25 ( 6 )   1376 - 1390   2017.06

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  • Michigan-style fuzzy GBML with (1+1)-ES generation update and multi-pattern rule generation Reviewed

    Y. Nojima, S. Takemura, K. Watanabe, and H. Ishibuchi

    Proc. of Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems 雑誌   2017.06

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    Kind of work:Joint Work  

  • Performance comparison of EMO algorithms on test problems with different search space shape

    Y. Tanigaki, Y. Nojima, and H. Ishibuchi

    Proc. of Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems 雑誌   2017.06

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  • FML-based prediction agent and its application to game of Go

    C.-S. Lee, M.-H. Wang, C.-H. Kao, S.-C. Yang, Y. Nojima, R. Saga, N. Shuo, and N. Kubota

    Proc. of Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems 雑誌   2017.06

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  • Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes Reviewed

    H. Ishibuchi, Y. Setoguchi, H. Masuda, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌 IEEE   21 ( 2 )   169 - 190   2017.04

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  • An efficient and effective approach for mining a group stock portfolio using MapReduce Reviewed

    C.-H. Chen, C.-C. Chen, and Y. Nojima

    Intelligent Data Analysis 雑誌 IOS Press   21 ( S1 )   S217 - S232   2017.04

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    Kind of work:Joint Work  

  • Hypervolume subset selection for triangular and inverted triangular Pareto fronts of three-objective problems Reviewed

    H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima

    Proc. of 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms   95 - 110   2017.01

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  • Mutation operators based on variable grouping for multi-objective large-scale optimization Reviewed

    H. Zille, H. Ishibuchi, S. Mostaghim, and Y. Nojima

    Proc. of 2016 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making   2016.12

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  • Difficulties of MOEA/D with Tchebycheff function for many-objective DTLZ 1-4 problems Reviewed

    H. Ishibuchi, K. Doi, and Y. Nojima

    Proc. of 7th International Symposium on Computational Intelligence and Industrial Applications   2016.11

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  • Fitting and overfitting of multi-objective fuzzy genetics-based machine learning to training data Reviewed

    H. Ishibuchi, S. Takemura, and Y. Nojima

    Proc. of 7th International Symposium on Computational Intelligence and Industrial Applications   2016.11

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    Kind of work:Joint Work  

  • Use of piecewise linear and nonlinear scalarizing functions in MOEA/D Reviewed

    H. Ishibuchi, K. Doi, and Y. Nojima

    Proc. of 14th International Conference on Parallel Problem Solving from Nature   503 - 523   2016.10

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    Kind of work:Joint Work  

  • Reference point specification in MOEA/D for multi-objective and many-objective problems Reviewed

    H. Ishibuchi, K. Doi, and Y. Nojima

    Proc. of 2016 IEEE International Conference on Systems, Man, and Cybernetics   4015 - 4020   2016.10

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    Kind of work:Joint Work  

  • Effects of different implementations of a real random number generator on the search behavior of multiobjective evolutionary algorithms Reviewed

    T. Funakoshi, Y. Nojima, and H. Ishibuchi

    Proc. of Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems   172 - 177   2016.08

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    Kind of work:Joint Work  

  • Weighted optimization framework for large-scale multi-objective optimization Reviewed

    H. Zille, H. Ishibuchi, S. Mostaghim, and Y. Nojima

    Companion of 2016 Genetic and Evolutionary Computation Conference   83 - 84   2016.07

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    Kind of work:Joint Work  

  • Performance comparison of NSGA-II and NSGA-III on various many-objective test problems Reviewed

    H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima

    Proc. of 2016 IEEE Congress on Evolutionary Computation   3045 - 3052   2016.07

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  • Common properties of scalable multiobjective problems and a new framework of test problems Reviewed

    H. Masuda, Y. Nojima, and H. Ishibuchi

    Proc. of 2016 IEEE Congress on Evolutionary Computation   3011 - 3018   2016.07

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    Kind of work:Joint Work  

  • Meta-optimization based multi-objective test problem generation using WFG toolkit Reviewed

    Y. Tanigaki, Y. Nojima, and H. Ishibuchi

    Proc. of 2016 IEEE Congress on Evolutionary Computation   2768 - 2775   2016.07

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    Kind of work:Joint Work  

  • Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms Reviewed

    Y. Nojima and H. Ishibuchi

    Proc. of 2016 IEEE Congress on Evolutionary Computation   2193 - 2200   2016.07

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    Kind of work:Joint Work  

  • How to compare many-objective algorithms under different settings of population and archive sizes Reviewed

    H. Ishibuchi, Y. Setoguchi, H. Masuda, and Y. Nojima

    Proc. of 2016 IEEE Congress on Evolutionary Computation   1149 - 1156   2016.07

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  • Characteristics of many-objective test problems and penalty parameter specification in MOEA/D Reviewed

    H. Ishibuchi, K. Doi, and Y. Nojima

    Proc. of 2016 IEEE Congress on Evolutionary Computation   1115 - 1122   2016.07

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  • Sensitivity of performance evaluation results by inverted generational distance to reference points Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    Proc. of 2016 IEEE Congress on Evolutionary Computation   1107 - 1114   2016.07

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  • Further analysis on strange evolution behavior of 7-bit binary string strategies in iterated prisoner’s dilemma game Reviewed

    T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi

    Proc. of 2016 IEEE Congress on Evolutionary Computation   335 - 342   2016.07

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    Kind of work:Joint Work  

  • Multiobjective fuzzy genetics-based machine learning with a reject option Reviewed

    Y. Nojima and H. Ishibuchi

    Proc. of 2016 IEEE International Conference on Fuzzy Systems   1405 - 1412   2016.07

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    Kind of work:Joint Work  

  • Interactive evolutionary computation with minimum fitness evaluation requirement and offline algorithm design Reviewed

    H. Ishibuchi, T. Sudo, and Y. Nojima

    SpringerPlus 雑誌 Springer   5   2016.02

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  • Relation between weight vectors and solutions in MOEA/D Reviewed

    H. Ishibuchi, K. Doi, H. Masuda, and Y. Nojima

    Proc. of 2015 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making 雑誌   861 - 868   2015.12

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    Kind of work:Joint Work  

  • Pareto fronts of many-objective degenerate test problems Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌 IEEE   20 ( 5 )   807 - 813   2015.12

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    Kind of work:Joint Work  

  • Variants of heuristic rule generation from multiple patterns in Michigan-style fuzzy genetics-based machine learning Reviewed

    Y. Nojima, K. Watanabe, and H. Ishibuchi

    Proc. of 2015 Conference on Technologies and Applications of Artificial Intelligence 雑誌   427 - 432   2015.11

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  • Simple modifications on heuristic rule generation and rule evaluation in Michigan-style fuzzy genetics-based machine learning Reviewed

    Y. Nojima, K. Watanabe, and H. Ishibuchi

    Proc. of 2015 IEEE International Conference on Fuzzy Systems 雑誌   2015.08

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  • Handling a training dataset as a black-box model for privacy preserving in fuzzy GBML algorithms Reviewed

    H. Ishibuchi and Y. Nojima

    Proc. of 2015 IEEE International Conference on Fuzzy Systems 雑誌   2015.08

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  • A study on performance evaluation ability of a modified inverted generational distance indicator Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    Proc. of Genetic and Evolutionary Computation Conference 雑誌   695 - 702   2015.07

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    Kind of work:Joint Work  

  • Algorithm structure optimization by choosing operators in multiobjective genetic local search Reviewed

    Y. Tanigaki, H. Masuda, Y. Setoguchi, Y. Nojima, and H. Ishibuchi

    Proc. of 2015 IEEE Congress on Evolutionary Computation 雑誌   854 - 861   2015.05

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  • Rotation effects of objective functions in parallel distributed multiobjective fuzzy genetics-based machine learning Reviewed

    Y. Takahashi, Y. Nojima, and H. Ishibuchi

    Proc. of 10th Asian Control Conference 雑誌   2015.05

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  • Strange evolution behavior of 7-bit binary string strategies in iterated prisoner's dilemma game Reviewed

    T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi

    Proc. of 2015 IEEE Congress on Evolutionary Computation 雑誌   3346 - 3353   2015.05

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    Kind of work:Joint Work  

  • Effects of heuristic rule generation from multiple patterns in multiobjective fuzzy genetics-based machine learning Reviewed

    Y. Nojima, K. Watanabe, and H. Ishibuchi

    Proc. of 2015 IEEE Congress on Evolutionary Computation 雑誌   2996 - 3003   2015.05

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  • Comparing solution sets of different size in evolutionary many-objective optimization Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    Proc. of 2015 IEEE Congress on Evolutionary Computation 雑誌   2859 - 2866   2015.05

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  • Effects of ensemble action selection with different usage of player's memory resource on the evolution of cooperative strategies for iterated prisoner's dilemma game Reviewed

    T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi

    Proc. of 2015 IEEE Congress on Evolutionary Computation 雑誌   1505 - 1512   2015.05

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  • Behavior of multi-objective evolutionary algorithms on many-objective knapsack problems Reviewed

    H. Ishibuchi, N. Akedo, and Y. Nojima

    IEEE Trans. on Evolutionary Computation 雑誌   19 ( 2 )   264 - 283   2015.04

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    Kind of work:Joint Work  

  • Application of parallel distributed implementation to multiobjective fuzzy genetics-based machine learning Reviewed

    Y. Nojima, Y. Takahashi, and H. Ishibuchi

    Lecture Notes in Computer Science 9011: Intelligent Information and Database Systems – ACIIDS 2015   462 - 471   2015.03

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  • Modified distance calculation in generational distance and inverted generational distance Reviewed

    H. Ishibuchi, H. Masuda, Y. Tanigaki, and Y. Nojima

    Lecture Notes in Computer Science 9018: Evolutionary Multi-Criterion Optimization – EMO 2015   110 - 125   2015.03

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  • Preference-based NSGA-II for many-objective knapsack problems Reviewed

    Y. Tanigaki, K. Narukawa, Y. Nojima, and H. Ishibuchi

    Proc. of 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems   637 - 642   2014.12

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  • Review of coevolutionary developments of evolutionary multi-objective and many-objective algorithms and test problems Reviewed

    H. Ishibuchi, H. Masuda, Y. Tanigaki, and Y. Nojima

    Proc. of 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making   178 - 185   2014.12

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  • Difficulties in specifying reference points to calculate the inverted generational distance for many-objective optimization problems Reviewed

    H. Ishibuchi, H. Masuda, Y. Tanigaki, and Y. Nojima

    Proc. of 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making   170 - 177   2014.12

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  • Genetic lateral tuning of membership functions as post-processing for hybrid fuzzy genetics-based machine learning Reviewed

    Y. Takahashi, Y. Nojima, and H. Ishibuchi

    Proc. of 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems   667 - 672   2014.12

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    Kind of work:Joint Work  

  • Offline design of interactive evolutionary algorithms with different genetic operators at each generation Reviewed

    H. Ishibuchi, T. Sudo, K. Ueba, and Y. Nojima

    Proc. of 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems   635 - 646   2014.11

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  • Application of fuzzy inference rules to early semi-automatic estimation of activity duration in software project management Reviewed

    C. H. Tan, K. S. Yap, H. Ishibuchi, Y. Nojima, and H. J. Yap

    IEEE Trans. on Human-Machine Systems 雑誌 IEEE   44 ( 5 )   678 - 688   2014.10

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  • Selecting a small number of non-dominated solutions to be presented to the decision maker Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    Proc. of 2014 IEEE International Conference on Systems, Man, and Cybernetics   3850 - 3855   2014.10

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  • Distance-based analysis of crossover operators for many-objective knapsack problems Reviewed

    H. Ishibuchi, Y. Tanigaki, H. Masuda, and Y. Nojima

    Lecture Notes in Computer Science 8672: Parallel Problem Solving from Nature – PPSN XIII   600 - 610   2014.09

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  • Hybrid fuzzy genetics-based machine learning with entropy-based inhomogeneous interval discretization Reviewed

    Y. Takahashi, Y. Nojima, and H. Ishibuchi

    Proc. of 2014 IEEE International Conference on Fuzzy Systems   1512 - 1517   2014.07

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  • Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: Multi-reference point approach to hypervolume maximization Reviewed

    H. Ishibuchi, H. Masuda, and Y. Nojima

    Companion of 2014 Genetic and Evolutionary Computation Conference   89 - 90   2014.07

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  • Effects of ensemble action selection on the evolution of iterated prisoner's dilemma game strategies Reviewed

    T. Sudo, Y. Nojima, and H. Ishibuchi

    Proc. of 2014 IEEE Congress on Evolutionary Computation   1195 - 1201   2014.07

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  • Visual examination of the behavior of EMO algorithms for many-objective optimization with many decision variables Reviewed

    H. Masuda, Y. Nojima, and H. Ishibuchi

    Proc. of 2014 IEEE Congress on Evolutionary Computation   2633 - 2640   2014.07

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  • Archive management in interactive evolutionary computation with minimum requirement for human user's fitness evaluation ability Reviewed

    H. Ishibuchi, T. Sudo, and Y. Nojima

    Lecture Notes in Computer Science 8467: Artificial Intelligence and Soft Computing – ICAISC 2014   360 - 371   2014.06

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  • Interactive (1+1) evolutionary strategy with one-fifth success rule Reviewed

    T. Sudo, K. Ueba, Y. Nojima, and H. Ishibuchi

    Proc. of 2nd Asia-Pacific Conference on Computer Aided System Engineering   294 - 300   2014.02

  • Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design Reviewed

    H. Ishibuchi and Y. Nojima

    Knowledge-Based Systems Elsevier   54   22 - 31   2013.12

  • Application of parallel distributed implementation to GAssist and its sensitivity analysis on the number of sub-populations and training data subsets Reviewed

    Y. Nojima, P. Ivarsson, and H. Ishibuchi

    Proc. of 14th International Symposium on Advanced Intelligent Systems   2013.11

  • Environmental selection schemes for rule removal in Michigan-style fuzzy genetics-based machine learning Reviewed

    Y. Nojima, Y. Takahashi, M. Yamane, and H. Ishibuchi

    Proc. of 14th International Symposium on Advanced Intelligent Systems   2013.11

  • Learning from multiple data sets with different missing attributes and privacy policies: Parallel distributed fuzzy genetics-based machine learning approach Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of IEEE Big Data 2013 Workshop on Scalable Machine Learning: Theory and Applications   63 - 70   2013.10

  • Effects of the number of opponents on the evolution of cooperation in the iterated prisoner’s dilemma Reviewed

    H. Ishibuchi, T. Sudo, K. Hoshino, and Y. Nojima

    Proc. of 2013 IEEE International Conference on Systems, Man, and Cybernetics   2001 - 2006   2013.10

  • Evolution of cooperative strategies for iterated prisoner’s dilemma on networks Reviewed

    H. Ishibuchi, T. Sudo, K. Hoshino, and Y. Nojima

    Proc. of Fifth International Conference on Computational Aspects of Social Networks   32 - 37   2013.08

  • Rule weight update in parallel distributed fuzzy genetics-based machine learning with data rotation Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of 2013 IEEE International Conference on Fuzzy Systems   2013.07

  • Many-objective and many-variable test problems for visual examination of multiobjective search Reviewed

    H. Ishibuchi, M. Yamane, N. Akedo, and Y. Nojima

    Proc. of 2013 IEEE Congress on Evolutionary Computation   1491 - 1498   2013.06

  • Difficulties in choosing a single final classifier from non-dominated solutions in multiobjective fuzzy genetics-based machine learning Reviewed

    H. Ishibuchi and Y. Nojima

    Proc. of 2013 Joint IFSA World Congress NAFIPS Annual Meeting   1203 - 1208   2013.06

  • How to strike a balance between local search and global search in multiobjective memetic algorithms for multiobjective 0/1 knapsack problems Reviewed

    H. Ishibuchi, Y. Tanigaki, N. Akedo, and Y. Nojima

    Proc. of 2013 IEEE Congress on Evolutionary Computation   1643 - 1650   2013.06

  • Parallel distributed hybrid fuzzy GBML models with rule set migration and training data rotation Reviewed

    H. Ishibuchi, S. Mihara, and Y. Nojima

    IEEE Transactions on Fuzzy Systems IEEE   21 ( 2 )   355 - 368   2013.04

  • Multiobjective genetic fuzzy rule selection with fuzzy relational rules Reviewed

    Y. Nojima and H. Ishibuchi

    Proc. of 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems   60 - 67   2013.04

  • Improving a fuzzy association rule-based classification model by granularity learning based on heuristic measures over multiple granularities Reviewed

    M. Fazzolari, R. Alcalá, Y. Nojima, H. Ishibuchi, and F. Herrera

    Proc. of 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems   44 - 51   2013.04

  • Effects of duplicated objectives in many-objective optimization problems on the search behavior of hypervolume-based evolutionary algorithms Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of 2013 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making   25 - 32   2013.04

  • Difficulty in evolutionary multiobjective optimization of discrete objective functions with different granularities Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of 7th International Conference on Evolutionary Multi-Criterion Optimization   230 - 245   2013.03

  • Relation between neighborhood size and MOEA/D performance on many-objective problems Reviewed

    H. Ishibuchi, N. Akedo, and Y. Nojima

    Proc. of 7th International Conference on Evolutionary Multi-Criterion Optimization   459 - 474   2013.03

  • A review of the application of multiobjective evolutionary fuzzy systems: Current status and further directions Reviewed

    M. Fazzolari, R. Alcalá, Y. Nojima, H. Ishibuchi, and F. Herrera

    IEEE Transactions on Fuzzy Systems IEEE   21 ( 1 )   45 - 65   2013.02

  • Problem formulation of interactive evolutionary computation with minimum requirement for human user’s fitness evaluation ability Reviewed

    H. Ishibuchi, K. Hoshino, and Y. Nojima

    Proc. of 16th Asia Pacific Symposium on Intelligent and Evolutionary Systems   52 - 57   2012.12

  • Ensemble fuzzy rule-based classifier design by parallel distributed fuzzy GBML algorithms Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of 9th International Conference on Simulated Evolution and Learning   93 - 103   2012.12

  • Comparison of different fitness functions in genetic fuzzy rule selection Reviewed

    M. Yamane, A. Ueda, N. Tadokoro, Y. Nojima, and H. Ishibuchi

    Proc. of Joint 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligent Systems   1046 - 1051   2012.11

  • Two-objective solution set optimization to maximize hypervolume and decision space diversity in multiobjective optimization Reviewed

    H. Ishibuchi, M. Yamane, N. Akedo, and Y. Nojima

    Proc. of Joint 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligent Systems   1871 - 1876   2012.11

  • Recombination of similar parents in SMS-EMOA on many-objective 0/1 knapsack problems Reviewed

    H. Ishibuchi, N. Akedo, and Y. Nojima

    Proc. of 12th International Conference on Parallel Problem Solving from Nature   132 - 142   2012.09

  • Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms Reviewed

    H. Ishibuchi, M. Yamane, and Y. Nojima

    Proc. of 2012 Genetic and Evolutionary Computation Conference   481 - 488   2012.07

  • Application of parallel distributed genetics-based machine learning to imbalanced data sets Reviewed

    Y. Nojima, S. Mihara, and H. Ishibuchi

    Proc. of 2012 IEEE International Conference on Fuzzy Systems   928 - 933   2012.06

  • Evolution of strategies in a spatial IPD Game with a number of different representation schemes Reviewed

    H. Ishibuchi, K. Hoshino, and Y. Nojima

    Proc. of 2012 IEEE Congress on Evolutionary Computation   808 - 815   2012.06

  • Strategy evolution in a spatial IPD game where each agent is not allowed to play against itself Reviewed

    H. Ishibuchi, K. Hoshino, and Y. Nojima

    Proc. of 2012 IEEE Congress on Evolutionary Computation   688 - 695   2012.06

  • EMO algorithms on correlated many-objective problems with different correlation strength Reviewed

    H. Ishibuchi, N. Akedo, and Y. Nojima

    Proc. of 2012 World Automation Congress   2012.06

  • Comparing predictive accuracy of a genetic Takagi-Sugeno fuzzy model and random forests for fish habitat modelling Reviewed

    S. Fukuda, B. De Baets, and Y. Nojima

    Proc. of International Workshop on Advanced Computational Intelligence and Intelligent Informatics   2011.12

  • Training data subdivision and periodical rotation in hybrid fuzzy genetics-based machine learning Reviewed

    H. Ishibuchi, S. Mihara, and Y. Nojima

    Proc. of 10th International Conference on Machine Learning and Applications   229 - 234   2011.12

  • Mobile robot controller design by evolutionary multiobjective optimization in multiagent environments Reviewed

    Y. Nojima and H. Ishibuchi

    Lecture Notes in Artificial Intelligence 7102: Intelligent Robotics and Applications   511 - 524   2011.12

  • Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions Reviewed

    R. Alcala, Y. Nojima, F. Herrera, and H. Ishibuchi

    Soft Computing Springer   15 ( 12 )   2303 - 2318   2011.11

  • Parallel distributed genetic rule selection of association rules

    Y. Nojima, S. Mihara, and H. Ishibuchi

    Abstract Booklet of International Workshop on Simulation and Modeling related to Computational Science and Robotics Technology   34 - 35   2011.11

  • Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning Reviewed

    H. Ishibuchi, Y. Nakashima, and Y. Nojima

    Soft Computing Springer   15 ( 12 )   2415 - 2434   2011.11

  • Relation between migration interval and data rotation interval in parallel distributed fuzzy GBML Reviewed

    S. Mihara. Y. Nojima, and H. Ishibuchi

    Proc. of 12th International Symposium on Advanced Intelligent Systems   346 - 349   2011.10

  • Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Soft Computing Springer   15 ( 9 )   1749 - 1767   2011.09

  • Effects of configuration of agents with different strategy representations on the evolution of cooperative behavior in a spatial IPD game Reviewed

    H. Ishibuchi, K. Takahashi, K. Hoshino, J. Maeda, and Y. Nojima

    Proc. of 2011 IEEE Conference on Computational Intelligence and Games   313 - 320   2011.08

  • A many-objective test problem for visually examining diversity maintenance behavior in a decision space Reviewed

    H. Ishibuchi, N. Akedo, and Y. Nojima

    Proc. of 2011 Genetic and Evolutionary Computation Conference   649 - 656   2011.07

  • Behavior of EMO algorithms on many-objective optimization problems with correlated objectives Reviewed

    H. Ishibuchi, N. Akedo, H. Ohyanagi, and Y. Nojima

    Proc. of 2011 IEEE Congress on Evolutionary Computation   2011.06

  • Toward quantitative definition of explanation ability of fuzzy rule-based classifiers Reviewed

    H. Ishibuchi and Y. Nojima

    Proc. of 2011 IEEE International Conference on Fuzzy Systems   549 - 566   2011.06

  • A meta-fuzzy classifier for specifying appropriate fuzzy partitions by genetic fuzzy rule selection with data complexity measures Reviewed

    Y. Nojima, S. Nishikawa, and H. Ishibuchi

    Proc. of 2011 IEEE International Conference on Fuzzy Systems   264 - 271   2011.06

  • Double cross-validation for performance evaluation of multi-objective genetic fuzzy systems Reviewed

    H. Ishibuchi, Y. Nakashima, and Y. Nojima

    Proc. of 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems   31 - 38   2011.04

  • Many-objective test problems with multiple Pareto optimal regions in a decision space Reviewed

    H. Ishibuchi, N. Akedo, H. Ohyanagi, Y. Hitotsuyanagi, and Y. Nojima

    Proc. of 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making   113 - 120   2011.04

  • Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D Reviewed

    H. Ishibuchi, Y. Hitotsuyanagi, H. Ohyanagi, and Y. Nojima

    Proc. of 6th International Conference on Evolutionary Multi-Criterion Optimization   166 - 181   2011.04

  • Evolution of strategies with different representation schemes in a spatial iterated prisoner’s dilemma game Reviewed

    H. Ishibuchi, H. Ohyanagi, and Y. Nojima

    IEEE Transactions on Computational Intelligence and AI in Games IEEE   3 ( 1 )   67 - 82   2011.03

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  • Design of linguistically interpretable fuzzy rule-based classifiers: A short review and open questions Reviewed

    H. Ishibuchi, Y. Kaisho, and Y. Nojima

    Journal of Multiple-Valued Logic and Soft Computing Old City Publishing   17 ( 41673 )   101 - 134   2011.03

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  • Diversity improvement by non-geometric binary crossover in evolutionary multiobjective optimization Reviewed

    H. Ishibuchi, N. Tsukamoto, and Y. Nojima

    IEEE Transactions on Evolutionary Computation IEEE   14 ( 6 )   985 - 998   2010.12

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  • Appropriate granularity specification for fuzzy classifier design by data complexity measures Reviewed

    S. Nishikawa, Y. Nojima, and H. Ishibuchi

    World Congress on Nature and Biologically Inspired Computing   698 - 703   2010.12

  • Multiobjectivization from two objectives to four objectives in evolutionary multi-objective optimization algorithms Reviewed

    H. Ishibuchi, Y. Hitotsuyanagi, Y. Nakashima, and Y. Nojima

    World Congress on Nature and Biologically Inspired Computing   509 - 514   2010.12

  • Use of multiple grids with different scalarizing functions in MOEA/D Reviewed

    H. Ishibuchi, Y. Sakane, and Y. Nojima

    Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems SOFT   898 - 903   2010.12

  • Parallel distributed implementation of genetics-based machine learning for fuzzy classifier design Reviewed

    Y. Nojima, S. Mihara, and H. Ishibuchi

    8th International Conference on Simulated Evolution and Learning Springer   309 - 318   2010.12

  • Rotation effect of training data subsets in parallel distributed fuzzy genetics-based nachine learning Reviewed

    Y. Nojima, S. Mihara and H. Ishibuchi

    14th Asia Pacific Symposium on Intelligent and Evolutionary Systems IES   2010.11

  • ow to choose solutions for local search in multiobjective combinatorial memetic algorithms Reviewed

    H. Ishibuchi, Y. Hitotsuyanagi, Y. Wakamatsu, and Y. Nojima

    11th International Conference on Parallel Problem Solving from Nature Springer   516 - 525   2010.09

  • Use of non-geometric binary crossover as mutation Reviewed

    H. Ishibuchi, N. Tsukamoto, and Y. Nojima

    2010 World Automation Congress WAC   2010.09

  • Many-objective test problems to visually examine the behavior of multiobjective evolution in a decision space Reviewed

    H. Ishibuchi, Y. Hitotsuyanagi, N. Tsukamoto, and Y. Nojima

    11th International Conference on Parallel Problem Solving from Nature Springer   91 - 100   2010.09

  • Indicatorに基づく進化型多目的最適化アルゴリズムへのHypervolume近似手法の適用 Reviewed

    塚本実孝,坂根悠治,能島裕介,石渕久生

    システム制御情報学会論文誌 システム制御情報学会   23 ( 8 )   165 - 177   2010.08

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  • 多目的遺伝的局所探索アルゴリズムにおける局所探索適用個体の選択 Reviewed

    一柳徳宏,若松良彦,能島裕介,石渕久生

    システム制御情報学会論文誌 システム制御情報学会   23 ( 8 )   178 - 187   2010.08

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  • Effects of fine fuzzy partitions on the generalization ability of evolutionary multi-objective fuzzy rule-based classifiers Reviewed

    H. Ishibuchi, Y. Nakashima, and Y. Nojima

    2010 IEEE International Conference on Fuzzy Systems IEEE   1238 - 1245   2010.07

  • Accuracy implementation of genetic fuzzy rule selection with candidate rule addition and membership tuning Reviewed

    Y. Nojima, Y. Kaisho, and H. Ishibuchi

    2010 IEEE International Conference on Fuzzy Systems IEEE   527 - 534   2010.07

  • Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets Reviewed

    Y. Nojima, S. Mihara, and H. Ishibuchi

    2010 IEEE Congress on Evolutionary Computation IEEE   2113 - 2120   2010.07

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  • Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions Reviewed

    H. Ishibuchi, N. Tsukamoto, Y. Sakane and Y. Nojima

    Genetic and Evolutionary Computation Conference - GECCO 2010, ACM   527 - 534   2010.07

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  • Simultaneous use of different scalarizing functions in MOEA/D Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto and Y. Nojima

    Genetic and Evolutionary Computation Conference - GECCO 2010, ACM   519 - 526   2010.07

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  • Simple changes in problem formulations make a difference in multiobjective genetic fuzzy systems Reviewed

    H. Ishibuchi, Y. Nakashima, and Y. Nojima

    Proc. of 4th International Workshop on Genetic and Evolutionary Fuzzy Systems 雑誌   2010.03

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  • Use of very small training data subsets in parallel distributed genetic fuzzy rule selection Reviewed

    Y. Nojima, H. Ishibuchi, and S. Mihara

    Proc. of 4th International Workshop on Genetic and Evolutionary Fuzzy Systems 雑誌   27 - 32   2010.03

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  • Use of multi-objective genetic rule selection for examining the effectiveness of inter-vehicle communication in traffic simulations Reviewed

    Yoshihiro Hamada, Yusuke Nojima, Hisao Ishibuchi

    Artificial Life and Robotics 雑誌   14 ( 3 )   410 - 413   2009.12

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  • Effects of including single-objective optimal solutions in an initial population on evolutionary multiobjective optimization Reviewed

    Y. Tsujimoto, Y. Hitotsuyanagi, Y. Nojima, and H. Ishibuchi

    Proc. of International Conference on Soft Computing and Pattern Recognition 雑誌   352 - 357   2009.12

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  • Effects of the user of multiple fuzzy partitions on the search ability of multiobjective fuzzy genetics-based machine learning Reviewed

    Y. Nojima, Y. Nakashima, and H. Ishibuchi

    Proc. of International Conference on Soft Computing and Pattern Recognition 雑誌   341 - 346   2009.12

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  • Application of interactive fuzzy data mining to the analysis of inter-vehicle communication in traffic simulations Reviewed

    Y. Nojima, Y. Hamada, and H. Ishibuchi

    ICGST International Journal on Automation, Robotics and Autonomous Systems 雑誌   9 ( 2 )   17 - 25   2009.12

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  • Incorporation of user preference into multi-objective genetic fuzzy rule selection for pattern classification problems Reviewed

    Y. Nojima and H. Ishibuchi

    Artificial Life and Robotics 雑誌   14 ( 3 )   418 - 421   2009.12

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  • Evolution of cooperative behavior among heterogeneous agents with different strategy representations in an iterated prisoner’s dilemma Reviewed

    H. Ohyanagi, Y. Wakamatsu, Y. Nakashima, Y. Nojima and H. Ishibuchi

    Artificial Life and Robotics 雑誌   14 ( 3 )   414 - 417   2009.12

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  • 進化型多目的最適化に対するスカラー化関数を用いたHypervolumeの近似手法の提案 Reviewed

    塚本実孝,坂根悠治,能島裕介,石渕久生

    システム制御情報学会誌 雑誌   22 ( 11 )   385 - 395   2009.11

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  • Effects of data reduction on the generalization ability of parallel distributed genetic fuzzy rule selection Reviewed

    Y. Nojima, H. Ishibuchi

    Proc. of 9th International Conference on Intelligent Systems Design and Applications 雑誌   96 - 101   2009.11

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  • Evolutionary many-objective optimization by NSGA-II and MOEA/D with large populations Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Proc. of 2009 IEEE International Conference on Systems, Man, and Cybernetics 雑誌   1820 - 1825   2009.10

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  • Evolution of cooperative behavior in a spatial Iterated Prisoner’s Dilemma game with different representation schemes of game strategies Reviewed

    H. Ishibuchi, H. Ohyanagi, and Y. Nojima

    Proc. of 2009 IEEE International Conference on Fuzzy Systems 雑誌   1568 - 1573   2009.08

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  • Complexity, interpretability and explanation capability of fuzzy rule-based classifiers Reviewed

    H. Ishibuchi, Y. Kaisho, and Y. Nojima

    Proc. of 2009 IEEE International Conference on Fuzzy Systems 雑誌   1730 - 1735   2009.08

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  • Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning Reviewed

    H. Ishibuchi, Y. Nakashima, and Y. Nojima

    Proc. of 2009 IEEE International Conference on Fuzzy Systems 雑誌   1724 - 1729   2009.08

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  • Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection Reviewed

    R. Alcala, Y. Nojima, F. Herrera, and H. Ishibuchi

    Proc. of 2009 IEEE International Conference on Fuzzy Systems 雑誌   1718 - 1723   2009.08

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  • Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Proc. of 2009 IEEE International Conference on Fuzzy Systems 雑誌   1609 - 1614   2009.08

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  • Single-objective and multi-objective formulations of solution selection for hypervolume maximization Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Proc. of 2009 Genetic and Evolutionary Computation Conference 雑誌   1831 - 1832   2009.07

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  • Interactive fuzzy modeling by evolutionary multiobjective optimization with user preference Reviewed

    Y. Nojima and H. Ishibuchi

    Proc. of 2009 IFSA World Congress and 2009 EUSFLAT Conference 雑誌   1839 - 1844   2009.07

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  • Discussions on interpretability of fuzzy systems using simple examples Reviewed

    H. Ishibuchi and Y. Nojima

    Proc. of 2009 IFSA World Congress and 2009 EUSFLAT Conference 雑誌   1649 - 1654   2009.07

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  • 多数目的最適化問題における進化型多目的最適化アルゴリズムの問題点とその改良手法に関する考察 Reviewed

    塚本実孝,能島裕介,石渕久生

    システム制御情報学会誌 雑誌   22 ( 6 )   220 - 228   2009.06

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  • Effects of using two neighborhood structures on the performance of cellular evolutionary algorithms for many-objective optimization Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Proc. of 2009 IEEE Congress on Evolutionary Computation 雑誌   2508 - 2515   2009.05

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  • Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization Reviewed

    H. Ishibuchi, N. Tsukamoto, Y. Sakane, and Y. Nojima

    Proc. of 2009 IEEE Congress on Evolutionary Computation 雑誌   530 - 537   2009.05

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  • Interactive genetic fuzzy rule selection through evolutionary multiobjective optimization with user preference Reviewed

    Y. Nojima and H. Ishibuchi

    Proc. of 2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making 雑誌   141 - 148   2009.04

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  • Adaptation of scalarizing functions in MOEA/D: An adaptive scalarizing function-based multiobjective evolutionary algorithm Reviewed

    H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima

    Proc. of 5th International Conference on Evolutionary Multi-Criterion Optimization 雑誌   438 - 452   2009.04

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  • Application of interactive fuzzy data mining to the analysis of inter-vehicle communication in traffic simulations

    Yusuke Nojima, Yoshihiro Hamada Hisao Ishibuchi

    Proc. of 5th International Conference on Sciences of Electronic, Technologies of Information and Telecommunications 雑誌   2009.03

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  • Use of biased neighborhood structures in multi-objective memetic algorithms Reviewed

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima

    Soft Computing 雑誌   13   1432 - 7643   2009.03

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  • Effects of non-geometric binary crossover on multiobjective 0/1 knapsack problems Reviewed

    Noritaka Tsukamoto, Yusuke Nojima, Hisao Ishibuchi

    Artificial Life and Robotics 雑誌   13 ( 2 )   434 - 437   2009.03

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  • Parallel distributed genetic fuzzy rule selection Reviewed

    Yusuke Nojima, Hisao Ishibuchi, Isao Kuwajima

    Soft Computing 雑誌   13 ( 5 )   511 - 519   2009.03

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  • Incorporation of user preference into multiobjective genetic fuzzy rule selection for pattern classification problems

    Yusuke Nojima, Hisao Ishibuchi

    Proc. of 14th International Symposium on Artificial Life and Robotics 雑誌   186 - 189   2009.02

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  • Pareto-optimal fuzzy rule mining with EMO algorithms and its improvement by heuristic initialization

    Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 14th International Symposium on Artificial Life and Robotics 雑誌   377 - 380   2009.02

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  • Hybridization of evolutionary multiobjective optimization algorithms by the adaptive use of scalarizing fitness function

    Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 14th International Symposium on Artificial Life and Robotics 雑誌   365 - 368   2009.02

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  • Use of multiobjective genetic rule selection for examining the effectiveness of inter-vehicle communication in traffic simulations

    Yoshihiro Hamada, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 14th International Symposium on Artificial Life and Robotics 雑誌   93 - 96   2009.02

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  • Evolution of cooperative behavior among heterogeneous agents with different strategy representations in an iterated prisoner's dilemma game

    H. Ohyanagi, Y. Wakamatsu, Y. Nakashima, Y. Nojima, H. Ishibuchi

    Proc. of 14th International Symposium on Artificial Life and Robotics 雑誌   102 - 105   2009.02

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  • Obtaining accurate classifiers with Pareto-optimal and near Pareto-optimal rules Reviewed

    Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi

    Artificial Life and Robotics 雑誌   13 ( 1 )   315 - 319   2008.12

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  • Use of local ranking in cellular genetic algorithms with two neighborhood structures Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 7th International Conference on Simulated Evolution and Learning 雑誌   309 - 318   2008.12

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  • Effects of constructing fuzzy discretization from crisp discretization for rule-based classifiers Reviewed

    Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi

    Artificial Life and Robotics 雑誌   13 ( 1 )   294 - 297   2008.12

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  • Evolutionary multiobjective fuzzy system design Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proc. of 2nd Workshop on Computing and Communications from Biological Systems: Theory and Applications 雑誌   2008.11

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  • Probabilistic use of heuristic moves in multiobjective genetic local search for flowshop scheduling Reviewed

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima

    Conference Handbook of the UK Operational Research Society 50th Annual Conference 雑誌   2008.09

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  • Effects of diversity measures on the design of ensemble classifiers by multiobjective genetic fuzzy rule selection with a multi-classifier coding scheme Reviewed

    Yusuke Nojima, Hisao Ishibuchi

    Proc. of Third International Workshop on Hybrid Artificial Intelligence Systems 雑誌   755 - 762   2008.09

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  • Maintaining the diversity of solutions by non-geometric binary crossover in genetic algorithms Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems 雑誌   1512 - 1517   2008.09

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  • Use of heuristic local search for single-objective optimization in multiobjective memetic algorithms Reviewed

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 10th International Conference on Parallel Problem Solving from Nature 雑誌   743 - 752   2008.09

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  • Examining the effect of elitism in cellular genetic algorithms using two neighborhood structures Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 10th International Conference on Parallel Problem Solving from Nature 雑誌   458 - 467   2008.09

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  • Balance between Local Search and Global Search in Multiobjective Memetic Algorithms for Many-Objective Optimization Problems Reviewed

    Yasuhiro Hitotsuyanagi, Yusuke Nojima, Hisao Ishibuchi

    Proc. of Workshop and Summer School on Evolutionary Computing Lecture Series by Pioneers 雑誌   22 - 25   2008.08

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  • An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization Reviewed

    Hisao Ishibuchi. Kaname Narukawa, Noritaka Tsukamoto, and Yusuke Nojima

    European Journal of Operational Research 雑誌   188 ( 1 )   57 - 75   2008.07

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  • Maintaining the diversity of solutions by non-geometric binary crossover: A worst one-max solver competition case study Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 2008 Genetic and Evolutionary Computation Conference 雑誌   1111 - 1112   2008.07

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  • Effectiveness of scalability improvement attempts on the performance of NSGA-II for many-objective problems Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima

    Proc. of 2008 Genetic and Evolutionary Computation Conference 雑誌   649 - 656   2008.07

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  • Scalability of multiobjective genetic local search to many-objective problems: Knapsack problem case studies Reviewed

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima

    Proc. of 2008 IEEE Congress on Evolutionary Computation 雑誌   3587 - 3594   2008.06

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  • Computational efficiency of parallel distributed genetic fuzzy rule selection for large data sets Reviewed

    Yusuke Nojima, Hisao Ishibuchi

    Proc. of Information Processing and Management of Uncertainty in Knowledge-based Systems 雑誌   1137 - 1142   2008.06

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  • Effectiveness of designing fuzzy rule-based classifiers from Pareto-optimal rules Reviewed

    Isao Kuwajima, Hisao Ishibuchi, Yusuke Nojima

    Proc. of 2008 IEEE International Conference on Fuzzy Systems 雑誌   1185 - 1192   2008.06

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  • Evolutionary many-objective optimization: A short review Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 2008 IEEE Congress on Evolutionary Computation 雑誌   2424 - 2431   2008.06

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  • A visual explanation system for explaining fuzzy reasoning results by fuzzy rule-based classifiers Reviewed

    Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima

    Proc. of 2008 North American Fuzzy Information Processing Society Conference, 雑誌   2008.05

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  • Behavior of evolutionary many-objective optimization Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 10th International Conference on Computer Modeling and Simulation 雑誌   266 - 271   2008.04

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  • Designing fuzzy rule-based classifiers that can visually explain their classification results to human users Reviewed

    Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima

    Proc. of 3rd International Workshop on Genetic and Evolving Fuzzy Systems 雑誌   2008.03

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  • Evolutionary many-objective optimization Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 3rd International Workshop on Genetic and Evolving Fuzzy Systems 雑誌   47 - 52   2008.03

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  • Obtaining accurate classifiers with Pareto-optimal and near Pareto-optimal rules

    Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 13th International Symposium on Artificial Life and Robotics 雑誌   195 - 198   2008.01

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  • Effects of non-geometric binary crossover on multiobjective 0/1 knapsack problems

    Noritaka Tsukamoto, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 13th International Symposium on Artificial Life and Robotics 雑誌   642 - 645   2008.01

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  • Effects of constructing fuzzy discretization from crisp discretization for rule-based classifiers

    Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 13th International Symposium on Artificial Life and Robotics 雑誌   203 - 206   2008.01

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  • Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design Reviewed

    Yusuke Nojima, Hisao Ishibuchi

    International Journal of Hybrid Intelligent Systems 雑誌 IOS Press   4 ( 3 )   157 - 169   2007.10

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  • Choosing extreme parents for diversity improvement in evolutionary multiobjective optimization algorithms Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 2007 IEEE International Conference on Systems, Man and Cybernetics 雑誌   1946 - 1951   2007.10

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  • A study on traffic information sharing through inter-vehicle communication Reviewed

    Ken Ohara, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 2007 IEEE Multi-conference on Systems and Control 雑誌   670 - 675   2007.10

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  • Effects of problem-specific local search schemes in a memetic EMO algorithm Reviewed

    Yasuhiro Hitotsuyanagi, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 8th International Symposium on Advanced Intelligent Systems 雑誌   402 - 407   2007.09

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  • Iterative approach to indicator-based multiobjective optimization Reviewed

    Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima

    Proc. of 2007 IEEE Congress on Evolutionary Computation 雑誌   3697 - 3704   2007.09

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  • An empirical study on the specification of the local search application probability in multiobjective memetic algorithms Reviewed

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima

    Proc. of 2007 IEEE Congress on Evolutionary Computation 雑誌   2788 - 2795   2007.09

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  • Effects of spatial structures on evolution of iterated prisoner's dilemma game strategies with probabilistic decision making Reviewed

    Ken Ohara, Yusuke Nojima, Yumeka Kitano, Hisao Ishibuchi

    Proc. of 2007 IEEE Congress on Evolutionary Computation 雑誌   4051 - 4058   2007.09

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  • Prescreening of candidate rules using association rule mining and Pareto-optimality in genetic rule selection Reviewed

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima

    Proc. of 11th International Conference on Knowledge Based Intelligent Information and Engineering Systems 雑誌   509 - 516   2007.09

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  • Implementation of elitism in cellular genetic algorithms Reviewed

    Hisao Ishibuchi, Ken Ohara, Yusuke Nojima

    Proc. of 8th International Symposium on Advanced Intelligent Systems 雑誌   169 - 174   2007.09

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  • A simulation study of route selection with inter-vehicle communication Reviewed

    Yoshihiro Hamada, Yusuke Nojima, Ken Ohara, Hisao Ishibuchi

    Proc. of 8th International Symposium on Advanced Intelligent Systems 雑誌   175 - 180   2007.09

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  • Relation between Pareto-optimal fuzzy rules and Pareto-optimal fuzzy rule sets Reviewed

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima

    Proc. of 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making 雑誌   42 - 49   2007.07

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  • Data set subdivision for parallel distributed implementation of genetic fuzzy rule selection Reviewed

    Yusuke Nojima, Isao Kuwajima, Hisao Ishibuchi

    Proc. of 2007 IEEE International Conference on Fuzzy Systems 雑誌   2006 - 2011   2007.07

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  • Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Noritaka Tsukamoto, Ken Ohara

    Proc. of 2007 Genetic and Evolutionary Computation Conference 雑誌   829 - 836   2007.07

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  • Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proc. of 4th International Conference on Evolutionary Multi-Criterion Optimization 雑誌   51 - 65   2007.03

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  • Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    International Journal of Approximate Reasoning 雑誌   44 ( 1 )   4 - 31   2007.01

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  • 交通渋滞解消のための大域的及び局所的最適化経路選択手法の性能調査 Reviewed

    大原健,能島裕介,石渕久生

    日本知能情報ファジィ学会誌 雑誌 日本知能情報ファジィ学会   18 ( 6 )   867 - 873   2006.12

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  • Designing fuzzy ensemble classifiers by evolutionary multiobjective optimization with an entropy-based diversity criterion Reviewed

    Yusuke Nojima, Hisao Ishibuchi

    Proc. of 6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence 雑誌   2006.12

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  • Finding simple fuzzy classification systems with high interpretability through multiobjective rule selection Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima

    Proc. of 10th International Conference on Knowledge Based Intelligent Information and Engineering Systems 雑誌   86 - 93   2006.11

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  • Comparison of search ability between genetic fuzzy rule selection and fuzzy genetics-based machine learning Reviewed

    Yusuke Nojima, Hisao Ishibuchi, Isao Kuwajima

    Proc. of 2006 International Symposium on Evolving Fuzzy Systems 雑誌   125 - 130   2006.09

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  • Driving evolutionary multiobjective search by a scalarizing fitness function Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Tsutomu Doi

    Proc. of Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on Advanced Intelligent Systems 雑誌   2198 - 2203   2006.09

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  • Accuracy-complexity tradeoff analysis in data mining by multiobjective genetic rule selection Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima

    Proc. of Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on Advanced Intelligent Systems 雑誌   2069 - 2074   2006.09

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  • Multiobjective association rule mining Reviewed

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima

    Proc. of PPSN Workshop on Multiobjective Problem Solving from Nature 雑誌   2006.09

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    Kind of work:Joint Work  

  • Effects of using two neighborhood structures in cellular genetic algorithms for function optimization Reviewed

    Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima

    Proc. of 9th International Conference on Parallel Problem Solving from Nature 雑誌   949 - 958   2006.09

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    Kind of work:Joint Work  

  • Incorporation of scalarizing fitness functions into evolutionary multiobjective optimization algorithms Reviewed

    Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima

    Proc. of 9th International Conference on Parallel Problem Solving from Nature 雑誌   493 - 502   2006.09

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    Kind of work:Joint Work  

  • Genetic rule selection as a postprocessing procedure in fuzzy data mining Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima

    Proc. of 2006 International Symposium on Evolving Fuzzy Systems 雑誌   286 - 291   2006.09

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    Kind of work:Joint Work  

  • Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    International Journal of Hybrid Intelligent Systems 雑誌 IOS Press   3 ( 3 )   129 - 145   2006.07

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    Kind of work:Joint Work  

  • Fuzzy data mining by heuristic rule extraction and multiobjective genetic rule selection Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima

    Proc. of 2006 IEEE International Conference on Fuzzy Systems 雑誌   7824 - 7831   2006.07

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    Kind of work:Joint Work  

  • Comparison between single-objective and multi-objective genetic algorithms: Performance comparison and performance measures Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Tsutomu Doi

    Proc. of 2006 Congress on Evolutionary Computation 雑誌   3959 - 3966   2006.07

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    Kind of work:Joint Work  

  • Multiobjective genetic rule selection as a data mining postprocessing procedure Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima

    Proc. of 2006 Genetic and Evolutionary Computation Conference 雑誌   2   1591 - 1592   2006.07

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    Kind of work:Joint Work  

  • Incorporation of decision maker’s preference into evolutionary multiobjective optimization algorithms Reviewed

    Hisao Ishibuchi, Yusuke Nojima, Kaname Narukawa, Tsutomu Doi

    Proc. of 2006 Genetic and Evolutionary Computation Conference 雑誌   1   741 - 742   2006.07

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    Kind of work:Joint Work  

  • Comparison between centralized global optimization and distributed local optimization for traffic jam avoidance Reviewed

    Ken Ohara, Yusuke Nojima, Hisao Ishibuchi

    Proc. of 2006 Genetic and Evolutionary Computation Conference Late Breaking Papers 雑誌   2006.07

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    Kind of work:Joint Work  

  • Tradeoff between accuracy and rule length in fuzzy rule-based classification systems for high-dimensional problems Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proc. of 11th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems 雑誌   1936 - 1943   2006.07

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    Kind of work:Joint Work  

  • Interpretability-Accuracy Tradeoff by Multiobjective Genetics-Based Machine Learning for Pattern Classification Problems Reviewed

    Yusuke Nojima, Hisao Ishibuchi

    Proceedings of The Eleventh International Symposium on Artificial Life and Robotics 2006 (AROB 11th'06) 雑誌   452 - 455   2006.01

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    Kind of work:Joint Work  

  • Handling of Overlapping Objective Vectors in Evolutionary Multiobjective Optimization Reviewed

    Hisao Ishibuchi, Kaname Narukawa, Yusuke Nojima

    International Journal of Computational Intelligence Research 雑誌   1 ( 1 )   2005.12

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    Kind of work:Joint Work  

  • Performance Evaluation of Evolutionary Multiobjective Approaches to the Design of Fuzzy Rule-Based Ensemble Classifiers Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proc. of 5th International Conference on Hybrid Intelligent Systems 雑誌   271 - 276   2005.11

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    Kind of work:Joint Work  

  • Multiobjective formulations of fuzzy rule-based classification system design Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proceedings of Fourth Conference of the European Society for Fuzzy Logic and Technology and 11 Rencontres Francophones sur la Logique Floue et ses Applications (EUSFLAT-LFA 2005) 雑誌   285 - 290   2005.09

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    Kind of work:Joint Work  

  • Effects of Similarity-Based Mating Scheme on Evolutionary Function Optimization Reviewed

    Kaname Narukawa, Yusuke Nojima, Hisao Ishibuchi

    Proceedings of 6th International Symposium on Advanced Intelligent Systems 雑誌   735 - 740   2005.09

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    Kind of work:Joint Work  

  • An Empirical Study on the Handling of Overlapping Solutions in Evolutionary Multiobjective Optimization Reviewed

    Hisaoi Ishibuchi, Kaname Narukawa, Yusuke Nojima

    Proceedings of 2005 Genetic and Evolutionary Computation Conference 雑誌   817 - 824   2005.06

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    Kind of work:Joint Work  

  • Modification of Evolutionary Multiobejective Optimization Algorithms for Multiobjective Design of Fuzzy Rule-Based Classification Systems Reviewed

    Kaname Narukawa, Yusuke Nojima, Hisao Ishibuchi

    Proceedings of The IEEE international conference on fuzzy systems (FuzzIEEE2005) 雑誌   809 - 814   2005.05

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    Kind of work:Joint Work  

  • Comparison between Fuzzy and Interval Partitions in Evolutionary Multiobjective Design of Rule-Based Classification Systems Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proceedings of The IEEE international conference on fuzzy systems (FuzzIEEE2005) 雑誌   430 - 435   2005.05

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    Kind of work:Joint Work  

  • Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm Reviewed

    Yusuke Nojima, Kaname Narukawa, Shiori Kaige, Hisao Ishibuchi

    Proceedings of the third International Conference on Evolutionary Multi-Criterion Optimization (EMO2005), (C.A. Coello Coello, A. H. Aguirre, E. Zitzler Eds, LNCS 3410) 雑誌   341 - 354   2005.03

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    Kind of work:Joint Work  

  • Multiobjective Fuzzy Genetics-Based Machine Learning Reviewed

    Hisao Ishibuchi, Yusuke Nojima

    Proceedings of the 1st Workshop on Genetic Fuzzy Systems (GFS05) 雑誌   2005.03

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    Kind of work:Joint Work  

  • Gesture Clustering and Imitative Behavior Generation for Partner Robots

    Yusuke Nojima, Naoyuki Kubota, Fumio Kojima

    Proc. of the 10th International Symposium on Artificial Life and Robotics 雑誌   2005.02

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    Kind of work:Joint Work  

  • Performance Comparison between Fuzzy Rules and Interval Rules in Rule-Based Classification Systems

    Satoshi Namba, Yusuke Nojima, Hisao Ishibuchi

    Proc. of the 10th International Symposium on Artificial Life and Robotics 雑誌   2005.02

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    Kind of work:Joint Work  

  • Imitative Behavior Generation for A Vision-Based Partner Robot Reviewed

    Naoyuki Kubota, Yusuke Nojima, Fumio Kojima

    Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems 雑誌   3080 - 3085   2004.09

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    Kind of work:Joint Work  

  • Trajectory Generation and Accumulation for Partner Robots Based on Structured Learning Reviewed

    Yusuke Nojima, Naoyuki Kubota, Fumio Kojima

    Proceedings of 2004 Congress on Evolutionary Computation 雑誌   19 - 23   2004.06

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    Kind of work:Joint Work  

  • Interactive Trajectory Generation using Evolutionary Programming for a Partner Robot Reviewed

    Naoyuki Kubota, Yusuke Nojima, Indra Adji Sulistijono, Fumio Kojima

    Proceedings of the 12th IEEE Workshop Robot and Human Interactive Communication RO-MAN 2003 雑誌   335 - 340   2003.10

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    Kind of work:Joint Work  

  • Trajectory Generation for Human-Friendly Behavior of Partner Robot using Fuzzy Evaluating Interactive Genetic Algorithm Reviewed

    Yusuke Nojima, Fumio Kojima, Naoyuki Kubota

    Proceedings of The IEEE International Symposium on Computational Intelligence in Robotics and Automation 雑誌   306 - 311   2003.07

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    Kind of work:Joint Work  

  • Local Episode-based Learning Multi-Objective Behavior Cooridination for a Mobile Robos in Dynamic Environment Reviewed

    Yusuke Nojima, Fumio Kojima, Naoyuki Kubota

    Proceedings of 2003 IEEE International Conference on Fuzzy Systems 雑誌   307 - 321   2003.05

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    Kind of work:Joint Work  

  • Local Episode-based Learning of A Mobile Robot in A Dynamic Environment Reviewed

    Yusuke Nojima, Fumio Kojima, Naoyuki Kubota

    Proceedings of The Third International Symposium on Human and Artificial Intelligence Systems 雑誌   384 - 388   2002.12

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    Kind of work:Joint Work  

  • 多目的行動調停に基づく移動ロボットの行動獲得 Reviewed

    能島裕介, 小島史男, 久保田直行

    日本機会学会論文集C編 雑誌   68 ( 671 )   2067 - 2073   2002.07

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    Kind of work:Joint Work  

  • Perception and Behavior of Pet Robots based on Emotional Model Reviewed

    Yusuke Nojima, Fumio Kojima, Naoyuki Kubota

    Proceedings of Knowledge Based Intelligent Information Engineering System & Allied Technologies 雑誌   859 - 867   2001.09

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    Kind of work:Joint Work  

  • Dual Learning for Perception and Behavior of Mobile Robots Reviewed

    Naoyuki Kubota, Yusuke Nojima, Fumio Kojima, Toshio Fukuda

    Proceedings of Joint 9th IFSA World Conference and 20th NAFIPS International Conference 雑誌   1401 - 1406   2001.07

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    Kind of work:Joint Work  

  • 学習機構を持つ自在搬送システムの最適化 Reviewed

    久保田直行, 能島裕介, 小島史男, 福田敏男

    日本機会学会論文集C編 雑誌   66 ( 652 )   3970 - 3976   2000.12

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    Kind of work:Joint Work  

  • Evolving Pet Robot with Emotional Model Reviewed

    Naoyuki Kubota, Yusuke Nojima, Norio BABA, Fumio Kojima, Toshio Fukuda

    Proceedings of Congress on Evolutionary Computation 2000 雑誌   1231 - 1237   2000.07

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    Kind of work:Joint Work  

  • Multi-objective Behavior Coordinate for A Mobile Robot with Fuzzy Neural Networks Reviewed

    Naoyuki Kubota, Yusuke Nojima, Fumio Kojima, Toshio Fukuda

    Proceedings of The IEEE-INNS-ENNS International Joint Conference on Neural Networks 雑誌   - 6   2000.07

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    Kind of work:Joint Work  

  • Control of Behavior Dimension for Mobile Robots Reviewed

    Yusuke Nojima, Naoyuki Kubota, Fumio Kojima, Toshio Fukuda

    Proceedings of The Forth Asian Fuzzy Systems Symposium 雑誌   652 - 657   2000.05

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    Kind of work:Joint Work  

  • Path Planning and Control for A Flexible Transfer System Reviewed

    Naoyuki Kubota, Yusuke Nojima, Fumio Kojima, Toshio Fukuda, Susumu Shibata

    Journal of Robotics & Mechatronics 雑誌   12 ( 2 )   2067 - 2073   2000.04

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    Kind of work:Joint Work  

  • Intelligent Control of Self-Organizing Manufacturing System with Local Learning Mechanism Reviewed

    Naoyuki Kubota, Yusuke Nojima, Fumio Kojima, Toshio Fukuda, Susumu Shibata

    Proceedings of The 25th Annual Conference of the IEEE Industrial Electronics Society 雑誌   - 6   1999.11

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    Kind of work:Joint Work  

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Books and Other Publications

  • Springer Handbook of Computational Intelligence

    H. Ishibuchi, Y. Nojima( Role: Joint author)

    Springer-Verlag Berlin Heidelberg  2015.05 

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    Responsible for pages:1479-1498  

  • Simulation and Modeling Related to Computational Science and Robotics Technology

    Y. Nojima, S. Mihara, and H. Ishibuchi( Role: Joint author)

    IOS Press  2012.08 

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    Responsible for pages:140-154  

  • 進化技術ハンドブック

    能島裕介,久保田直行( Role: Joint author)

    近代科学社  2011.11 

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    Responsible for pages:453-459  

  • Computational Intelligence: Collaboration, Fusion and Emergence

    Hisao Ishibuchi, Yusuke Nojima( Role: Joint author)

    Springer  2009.07 

  • Multi-Objective Memetic Algorithms

    Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima( Role: Joint author)

    Springer  2009.02 

  • Computational Intelligence: A Compendium

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima( Role: Joint author)

    Springer  2008.07 

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    Responsible for pages:641-685  

  • Multi-objective Evolutionary Algorithms for Knowledge Discovery from Databases

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima( Role: Joint author)

    Springer  2008.03 

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    Responsible for pages:47-70  

  • Multiobjective Problem Solving from Nature: From Concepts to Applications

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima( Role: Joint author)

    Springer  2008.01 

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    Responsible for pages:219-240  

  • Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision

    Hisao Ishibuchi, Yusuke Nojima( Role: Joint author)

    Springer  2007.11 

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    Responsible for pages:377-395  

  • Lecture Notes in Computer Science 4693: Knowledge-Based Intelligent Information and Engineering Systems - KES 2007

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima( Role: Joint author)

    Springer  2007.09 

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    Responsible for pages:509-516  

  • Analysis and Design of Intelligent Systems using Soft Computing Techniques

    Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima( Role: Joint author)

    Springer  2007.08 

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    Responsible for pages:387-396  

  • Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO2007

    Hisao Ishibuchi, Yusuke Nojima( Role: Joint author)

    Springer  2007.03 

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    Responsible for pages:51-65  

  • Lecture Notes in Computer Science 4252: Knowledge-Based Intelligent Information and Engineering Systems - KES 2006

    Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima( Role: Joint author)

    Springer  2006.10 

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    Responsible for pages:86-93  

  • Lecture Notes in Computer Science 4193: Parallel Problem Solving from Nature - PPSN IX

    Hisao Ishibuchi, Tsutomu Doi, Yusule Nojima( Role: Joint author)

    Springer  2006.09 

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    Responsible for pages:949-958  

  • Multi-Objective Machine Learning

    Hisao Ishibuchi, Yusuke Nojima( Role: Joint author)

    Springer  2006.03 

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    Responsible for pages:507-532  

  • Lecture Notes in Computer Science 3410: Evolutionary Multi-Criterion Optimization - EMO 2005

    Yusuke Nojima, Kaname Narukawa, Shiori Kaige, Hisaoi Ishibuchi( Role: Joint author)

    Springer  2005.03 

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    Responsible for pages:341-354  

  • Dynamic Systems Approach for Embodiment and Sociality -From Ecological Psychology to Robotics-

    Yusuke Nojima, Fumio Kojima, Naoyuki Kubota( Role: Joint author)

    Advanced Knowledge International  2003.10 

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    Responsible for pages:318-322  

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MISC

  • オープンスペースディスカッション2021実施報告 Invited

    能島裕介, 高木英行, 棟朝雅晴, 濱田直希, 西原慧, 高玉圭樹, 佐藤寛之, 桐淵大貴, 宮川みなみ

    進化計算学会論文誌   13 ( 1 )   1 - 9   2022

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    Authorship:Lead author   Kind of work:Joint Work  

  • SOFT-CR連携ファジィ学問塾2019開催報告 International journal

    本多 克宏, 能島 裕介, 中島 智晴

    知能と情報   31 ( 6 )   172 - 173   2019( ISSN:1347-7986

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    Publishing type:Meeting report   Kind of work:Joint Work   International / domestic magazine:Domestic journal  

    DOI: 10.3156/jsoft.31.6_172

    CiNii Article

Presentations

  • 親個体選択戦略の変更による2目的変換に基づくマルチモーダル多目的最適化アルゴリズムの改良 Domestic conference

    徳坂光彦,増山直輝,能島裕介

    第25回進化計算学会研究会  2024.03 

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    Presentation type:Oral presentation (general)  

  • Integrating white and black box techniques for interpretable machine learning International conference

    E. M. Vernon, N. Masuyama, and Y. Nojima

    9th International Congress on Information and Communication Technology  2024.02 

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    Presentation type:Oral presentation (general)  

  • Riesz s-energy indicators for diversity assessment of multiobjective evolutionary algorithms International conference

    T. Kinoshita, N. Masuyama, and Y. Nojima

    24th International Symposium on Intelligent Systems  2023.12 

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    Presentation type:Oral presentation (general)  

  • Effects of parent selection schemes on the search performance of multi-modal multi-objective evolutionary algorithm with problem transformation into two-objective subproblems International conference

    Y. Nojima, T. Tokusaka, and N. Masuyama

    24th International Symposium on Intelligent Systems  2023.12 

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    Presentation type:Oral presentation (general)  

  • ε-局所差分プライバシを用いた連合サロゲート進化型多目的最適化フレームワークの検討 Domestic conference

    木下貴登,増山直輝,能島裕介,石渕久生

    第17回進化計算シンポジウム2023  2023.12 

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    Presentation type:Oral presentation (general)  

  • アーカイブ個体群を用いた2段階ファジィ遺伝的機械学習の検討 Domestic conference

    小西豪,増山直輝,能島裕介

    第39回ファジィシステムシンポジウム  2023.09 

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    Presentation type:Oral presentation (general)  

  • 応共鳴理論に基づく階層的トポロジカルクラスタリングにおけるクラスタリング性能向上方法の検討 Domestic conference

    鳥越大貴,田代一貴,増山直輝,能島裕介,伊藤諒適,三宅寿英,馬野元秀

    第39回ファジィシステムシンポジウム  2023.09 

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    Presentation type:Oral presentation (general)  

  • 適応共鳴理論に基づくクラスタリングによるマルチラベル識別器の量質混在データへの対応 Domestic conference

    西川毅,増山直輝,能島裕介

    第39回ファジィシステムシンポジウム  2023.09 

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    Presentation type:Oral presentation (general)  

  • ε-局所差分プライバシを考慮した適応共鳴理論に基づく連合クラスタリング手法の検討 Domestic conference

    上田裕也,増山直輝,能島裕介

    第39回ファジィシステムシンポジウム  2023.09 

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  • 制約付き問題のための適応的問題分割ベース進化型多目的最適化アルゴリズムの検討 Domestic conference

    木下貴登,増山直輝,能島裕介

    第39回ファジィシステムシンポジウム  2023.09 

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    Presentation type:Oral presentation (general)  

  • Overview of techniques for rule extraction from neural networks Domestic conference

    2023.09 

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    Presentation type:Oral presentation (general)  

  • 実世界多目的最適化問題のためのRiesz discrete s-Energy によるConvergence-Diversity Diagramの拡張 Domestic conference

    木下貴登,増山直輝,能島裕介

    第24回進化計算学会研究会  2023.09 

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    Presentation type:Oral presentation (general)  

  • Effects of complexity enhancements on the search performance of multiobjective fuzzy genetics-based machine learning International conference

    T. Konishi, N. Masuyama, and Y. Nojima

    20th World Congress of the International Fuzzy Systems Association  2023.08 

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    Presentation type:Oral presentation (general)  

  • Fuzzy Classifiers with a two-stage reject option International conference

    Y. Nojima, K. Kawano, H. Shimahara, E. Vernon, N. Masuyama, and H. Ishibuchi

    2023 IEEE International Conference on Fuzzy Systems  2023.08 

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    Presentation type:Oral presentation (general)  

  • A decomposition-based multi-modal multi-objective evolutionary algorithm with problem transformation into two-objective subproblems International conference

    Y. Nojima, Y. Fujii, N. Masuyama, Y. Liu, and H. Ishibuchi

    2023 Genetic and Evolutionary Computation  2023.07 

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    Presentation type:Oral presentation (general)  

  • 適応共鳴理論に基づくクラスタリング手法によるマルチラベル識別器の改良

    西川毅,増山直輝,能島裕介,石渕久生

    2022 

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    Presentation type:Oral presentation (general)  

  • Effects of accuracy-based single-objective optimization in multiobjective fuzzy genetics-based machine learning

    T. Konishi, N. Masuyama, and Y. Nojima

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022)  2022 

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    Presentation type:Oral presentation (general)  

  • Search process analysis of multiobjective evolutionary algorithms using convergence-diversity diagram

    T. Kinoshita, N. Masuyama, and Y. Nojima

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022)  2022 

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    Presentation type:Oral presentation (general)  

  • Error-reject tradeoff analysis on two-stage classifier design with a reject option

    E. M. Vernon, N. Masuyama, and Y. Nojima

    World Automation Congress (WAC 2022)  2022 

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    Presentation type:Oral presentation (general)  

  • Behavior analysis of constrained multiobjective evolutionary algorithms using scalable constrained multi-modal distance minimization problems

    M. Yano, N. Masuyama, and Y. Nojima

    World Automation Congress (WAC 2022)  2022 

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    Presentation type:Oral presentation (general)  

  • Analytical methods to separately evaluate convergence and diversity for multi-objectiveoptimization

    T. Kinoshita, N. Masuyama, Y. Nojima, and H. Ishibuchi

    14th International Conference of Metaheuristics (MIC 2022)  2022 

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    Presentation type:Oral presentation (general)  

  • Evolutionary multiobjective multi-tasking for fuzzy genetics-based machine learning in multi-label classification

    Y. Omozaki, N. Masuyama, Y. Nojima, and H. Ishibuchi

    2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)  2022 

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    Presentation type:Oral presentation (general)  

  • Adaptive resonance theory-based clustering for handling mixed data

    N. Masuyama, Y. Nojima, H. Ishibuchi, and Z. Liu

    2022 International Joint Conference on Neural Networks (IJCNN)  2022 

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    Presentation type:Oral presentation (general)  

  • Convergence-Diversity Diagramのためのパレート最適近似手法の検討

    木下貴登,増山直輝,能島裕介,石渕久生

    2022 

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    Presentation type:Oral presentation (general)  

  • Accuracy-Rejection Tradeoff Analysis in Fuzzy Classifiers with a Two-Stage Reject Option International coauthorship Domestic conference

    Kawano Koyo, Vernon Eric, Masuyama Naoki, Nojima Yusuke, Ishibuchi Hisao

    Proceedings of the Fuzzy System Symposium  2022  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>In general, fuzzy classifiers have high interpretability because fuzzy classifiers can linguistically explain the classification reason by fuzzy sets used in the antecedent conditions of rules. A reject option that rejects patterns near the boundaries between different classes is an approach to increase the reliability of fuzzy classifiers. However, the conventional threshold-based reject option may reject more patterns than necessary to achieve high reliability. In this paper, we propose a two-stage reject option where after the threshold-based decision, the k-nearest neighbor is used for patterns with low confidence value than the threshold. If the class labels predicted by the k-nearest neighbor and the fuzzy classifier are the same, the fuzzy classifier outputs the predicted class label without rejection. Through computational experiments, we discuss the relationship between accuracy and the rejection rate.</p>

    DOI: 10.14864/fss.38.0_250

  • Comparison of Different Hierarchical Implementations in Topological Clustering with a Hierarchical Structure International coauthorship Domestic conference

    Tashiro Kazuki, Masuyama Naoki, Nojima Yusuke, Ishibuchi Hisao

    Proceedings of the Fuzzy System Symposium  2022  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>A topological clustering algorithm can adaptively generate networks consisting of nodes and edges to approximate the data distribution. In our previous study, we proposed a topological clustering algorithm with a hierarchical structure to extract a hierarchical structure of the entire data while performing clustering. However, this algorithm does not utilize the information of clusters because each node holds the data that contributed to the creation of the node, and the data is independently used as the training data for the next layer. For improving clustering performance, this paper proposes an approach to aggregate the data that contributed to the creation of nodes in the same cluster and to utilize the aggregated data as training data for the next layer. Based on experimental results using artificial and real-world datasets, the characteristics of the proposed algorithm are discussed.</p>

    DOI: 10.14864/fss.38.0_702

  • Multiobjective Fuzzy Genetics-based Machine Learning with Accuracy-Oriented Pre-Optimization International coauthorship Domestic conference

    Konishi Takeru, Masuyama Naoki, Nojima Yusuke, Ishibuchi Hisao

    Proceedings of the Fuzzy System Symposium  2022  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>Fuzzy classifier design requires maximization of classification accuracy and minimization of complexity. Multiobjective Fuzzy Genetics-Based Machine Learning (MoFGBL) can efficiently obtain a set of fuzzy classifiers considering the above-mentioned two objectives at the same time using an evolutionary multiobjective optimization algorithm. However, the search by MoFGBML is biased to minimize the complexity, and it is easy to obtain classifiers with low complexity. At the same time, it is difficult to obtain classifiers with high classification accuracy. In this paper, we propose a two-stage MoFGBML, which first performs accuracy-oriented single-objective optimization to obtain a set of accurate classifiers with a large number of rules. Then, multiobjective optimization is performed to obtain a wide variety of classifiers, from highly-accurate ones to simple ones.</p>

    DOI: 10.14864/fss.38.0_628

  • Evolutionary Design Optimization of Economic Support Policies by Social Simulations International coauthorship Domestic conference

    Nakagawa Yuto, Kinoshita Takato, Masuyama Naoki, Nojima Yusuke, Ishibuchi Hisao

    Proceedings of the Fuzzy System Symposium  2022  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>In recent years, severe economic damages have been caused by the spread of the Covid-19 infection. The design of economic support policies using social simulations has been paid great attention. In the Evolutionary Computation Competition 2021, a multiobjective optimization problem was posed to design economic support policies that simultaneously optimize the elimination of impoverished conditions and an appropriate level of payments. Economic support policies are evaluated using a social simulation with synthetic population data and multiple economic shock scenarios. In this paper, we apply an evolutionary multiobjective optimization algorithm to the design of promising economic support policies. We analyze the characteristics of Pareto optimal economic support policies and the structure of the multiobjective optimization problem through computational experiments.</p>

    DOI: 10.14864/fss.38.0_326

  • Incorporating Fairness Measures into Multiobjective Fuzzy Genetics-based Machine Learning International coauthorship Domestic conference

    Hiroki Nishiura, Masuyama Naoki, Nojima Yusuke, Ishibuchi Hisao

    Proceedings of the Fuzzy System Symposium  2022  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>In recent years, pattern classification has been used for various real-world problems. However, there may be a bias toward certain attributes in data collection. This may result in inappropriate classification biased toward particular social groups. For example, when designing a classifier that recommends whether an applicant should be hired or not for recruitment problems, there is a possibility that attributes such as race and gender affect hiring outcomes. So far, we have developed multiobjective fuzzy genetics-based machine learning (MoFGBML) considering classification performance and interpretability. This paper incorporates two fairness measures into MoFGBML to design fuzzy classifiers considering classification performance, interpretability, and fairness.</p>

    DOI: 10.14864/fss.38.0_256

  • Effects of different optimization formulations in evolutionary reinforcement learning on diverse behavior generation International conference

    V. Villin, N. Masuyama, and Y. Nojima

    2021 IEEE Symposium Series on Computational Intelligence  2021.12 

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    Presentation type:Oral presentation (general)  

  • Hierarchical topological clustering with automatic parameter estimation International conference

    Y. Yamada, N. Amako, N. Masuyama, Y. Nojima, and H. Ishibuchi

    The 22th International Symposium on Advanced Intelligent Systems  2021.12 

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    Presentation type:Oral presentation (general)  

  • Validation data accuracy as an additional objective in multiobjective fuzzy genetics-based machine learning International conference

    S. A. F. Dilone, N. Masuyama, Y. Nojima, and H. Ishibuchi

    The 22th International Symposium on Advanced Intelligent Systems  2021.12 

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    Presentation type:Oral presentation (general)  

  • Multi-modal multi-objective traveling salesman problem and its evolutionary optimizer International conference

    Y. Liu, L. Xu, Y. Han, N. Masuyama, Y. Nojima, H. Ishibuchi, and G. G. Yen

    2021 IEEE International Conference on Systems, Man, and Cybernetics  2021.10 

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    Presentation type:Oral presentation (general)  

  • 適応共鳴理論に基づくクラスタリングを用いた進化型多目的最適化アルゴリズム Domestic conference

    木下貴登,増山直輝,能島裕介,石渕久生

    第20回進化計算学会研究会  2021.09 

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    Presentation type:Oral presentation (general)  

  • 適応共鳴理論に基づくトポロジカルクラスタリングのための警戒パラメータの自動推定手法 Domestic conference

    尼子就都,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • マルチラベル識別問題のための適応共鳴理論に基づくトポロジカルクラスタリング Domestic conference

    吉永貴政,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • 複数の閾値を用いた棄却オプションの導入におけるファジィ識別器への影響調査 Domestic conference

    川野弘陽,Eric Vernon,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • 属性ごとに異なる形状のメンバシップ関数を用いたファジィ識別器設計 Domestic conference

    瀧川弘毅,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • パラメータの自動設定機構を導入した階層的トポロジカルクラスタリング Domestic conference

    山田友菜,増山直輝,能島裕介,石渕久生

    インテリジェント・システム・シンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • 多目的ファジィ遺伝的機械学習におけるルール追加型ミシガン操作 Domestic conference

    面崎祐一,増山直輝,能島裕介,石渕久生

    インテリジェント・システム・シンポジウム2021  2021.09 

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    Presentation type:Oral presentation (general)  

  • クラスタリング手法を用いた適応的分割に基づく進化型多目的最適化アルゴリズムの性能評価 Domestic conference

    木下貴登,増山直輝,能島裕介,石渕久生

    第14回進化計算シンポジウム2020  2020.12 

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    Presentation type:Oral presentation (general)  

  • 制約付き多目的マルチモーダル距離最小化問題 Domestic conference

    矢野真綾,増山直輝,能島裕介,石渕久生

    第14回進化計算シンポジウム2020  2020.12 

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    Presentation type:Oral presentation (general)  

  • Multi-label classification based on adaptive resonance theory International conference

    N. Masuyama, Y. Nojima, C. K. Loo, and H. Ishibuchi

    2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020)  2020.12 

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    Presentation type:Oral presentation (general)  

  • 複数データを用いた進化型多目的最適化による畳み込みニューラルネットワークのハイパーパラメータ最適化 Domestic conference

    夏目和弥,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2020  2020.09 

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    Presentation type:Oral presentation (general)  

  • 2目的最適化問題への変換に基づく進化型マルチモーダル多目的最適化アルゴリズム Domestic conference

    藤井祐人,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2020  2020.09 

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    Presentation type:Oral presentation (general)  

  • マルチラベル識別問題におけるファジィ遺伝的機械学習の多目的最適化と多数目的最適化の比較 Domestic conference

    面崎祐一,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2020  2020.09 

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    Presentation type:Oral presentation (general)  

  • 少数派クラスの識別性能を高めたMichigan型ファジィ遺伝的機械学習手法 Domestic conference

    西原光洋,増山直輝,能島裕介,石渕久生

    ファジィシステムシンポジウム2020  2020.09 

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    Presentation type:Oral presentation (general)  

  • 適応共鳴理論に基づいたトポロジカルクラスタリング手法による識別器設計 Domestic conference

    坪田一希,増山直輝,能島裕介,尼子就都,石渕久生

    ファジィシステムシンポジウム2020  2020.09 

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    Presentation type:Oral presentation (general)  

  • Divisive hierarchical clustering based on adaptive resonance theory International conference

    Y. Yamada, N. Masuyama, N. Amako, Y. Nojima, C. K. Loo, and H. Ishibuchi

    2020 International Symposium on Community-centric Systems (CcS 2020)  2020.09 

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    Presentation type:Oral presentation (general)  

  • Multilayer clustering based on adaptive resonance theory for noisy environments International conference

    N. Amako, N. Masuyama, C. K. Loo, Y. Nojima, Y. Liu, and H. Ishibuchi

    2020 International Joint Conference on Neural Networks (IJCNN 2020)  2020.07 

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    Presentation type:Oral presentation (general)  

  • Effects of local mating in inter-task crossover on the performance of decomposition-based evolutionary multiobjective multitask optimization algorithms International conference

    R. Hashimoto, T. Urita, N. Masuyama, Y. Nojima, and H. Ishibuchi

    2020 IEEE Congress on Evolutionary Computation (CEC 2020)  2020.07 

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    Presentation type:Oral presentation (general)  

  • On the normalization in evolutionary multi-modal multi-objective optimization International conference

    Y. Liu, H. Ishibuchi, G. G. Yen, Y. Nojima, N. Masuyama, and Y. Han

    2020 IEEE Congress on Evolutionary Computation (CEC 2020)  2020.07 

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    Presentation type:Oral presentation (general)  

  • Multiobjective fuzzy genetics-based machine learning for multi-label classification International conference

    Y. Omozaki, N. Masuyama, Y. Nojima, and H. Ishibuchi

    2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020)  2020.07 

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    Presentation type:Oral presentation (general)  

  • Towards realistic optimization benchmarks: A questionnaire on the properties of real-world problems International conference

    K. v. d. Blom, T. M. Deist, T. Tusar, M. Marchi, Y. Nojima, A. Oyama, V. Volz, and B. Naujoks

    2020 Genetic and Evolutionary Computation Conference  2020.07 

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    Presentation type:Oral presentation (general)  

  • Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms International conference

    H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima

    2020 Genetic and Evolutionary Computation Conference  2020.07 

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    Presentation type:Oral presentation (general)  

  • Many-objective problems are not always difficult for Pareto dominance-based evolutionary algorithms International conference

    H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima

    24th European Conference on Artificial Intelligence (ECAI 2020)  2020.06 

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    Presentation type:Oral presentation (general)  

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Outline of collaborative research (seeds)

  • 進化型多目的最適化

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    実世界の最適化問題には,同時に最適化すべき複数の相反する目的が存在する.進化型多目的最適化は複数のパレート最適解を手法の1回の実行で獲得可能である.

  • ファジィルールシステムの学習と獲得

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    学習対象の入出力データからファジィルールモデルを構築したり,新たなデータに基づいて再学習するファジィルールシステムを開発し,実問題への応用を試みる.

Grant-in-Aid for Scientific Research

  • Development of Evolutionary Multiobjective Optimization Algorithms and Benchmark Problem Design based on the Analysis of Real-world Problems

    Grant-in-Aid for Scientific Research(B)  2025

  • Development of Evolutionary Multiobjective Optimization Algorithms and Benchmark Problem Design based on the Analysis of Real-world Problems

    Grant-in-Aid for Scientific Research(B)  2024

  • 実問題解析に基づく進化型多目的最適化アルゴリズムおよびベンチマーク問題の開発

    2023

  • 実問題解析に基づく進化型多目的最適化アルゴリズムおよびベンチマーク問題の開発

    2022

  • 多目的進化型機械学習によるルール集合に基づく解釈可能な知識の獲得

    2022

  • 多目的進化型機械学習によるルール集合に基づく解釈可能な知識の獲得

    2021

  • 多目的進化型機械学習によるルール集合に基づく解釈可能な知識の獲得

    2020

  • 多目的進化型機械学習によるルール集合に基づく解釈可能な知識の獲得

    2019

  • 多目的遺伝的機械学習手法による大規模多属性データからの知識獲得

    2018

  • 多目的遺伝的機械学習手法による大規模多属性データからの知識獲得

    2017

  • 多目的遺伝的機械学習手法による大規模多属性データからの知識獲得

    2016

  • 多目的遺伝的機械学習手法の並列分散実装

    2015

  • 多目的遺伝的機械学習手法の並列分散実装

    2014

  • 多目的遺伝的機械学習手法の並列分散実装

    2013

  • 並列分散遺伝的知識獲得における効率的な個体群およびデータの分割

    2012

  • 第4回知能ロボットとその応用に関する国際会議

    2011

  • 並列分散遺伝的知識獲得における効率的な個体群およびデータの分割

    2011

  • 並列分散遺伝的知識獲得における効率的な個体群およびデータの分割

    2010

  • 並列分散遺伝的知識獲得における効率的な個体群およびデータの分割

    2009

  • ソフトコンピューティングとパターン認識に関する国際会議

    2009

  • 国際ファジィ協会およびヨーロッパファジィ学会の2009年国際会議

    2009

  • 第6回ハイブリッド知的システムに関する国際会議

    2006

  • ファジィシステム設計のための設計者の評価に基づく進化型多目的最適化手法の開発

    2005

  • ヨーロッパファジィ学会第4回会議

    2005

  • 進化型多目的最適化アルゴリズムの開発と多目的知識獲得への応用

    2005

  • ファジィシステムに関する2005年IEEE国際会議

    2005

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Charge of on-campus class subject

  • 情報工学基礎演習1

    2024   Weekly class   Undergraduate

  • 基幹情報学特別演習1

    2024   Weekly class   Graduate school

  • データマイニング

    2024   Weekly class   Graduate school

  • 基幹情報学特別研究2

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究1

    2024   Intensive lecture   Graduate school

  • プログラミング演習(機械学習演習)

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別演習I-1

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究8

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究7

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究5

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究3

    2024   Intensive lecture   Graduate school

  • 電気・情報系特別研究第三

    2024   Intensive lecture   Graduate school

  • 電気・情報系特別演習第三

    2024   Intensive lecture   Graduate school

  • 電気・情報系特別演習第一

    2024   Intensive lecture   Graduate school

  • 情報工学英語演習

    2024   Intensive lecture   Undergraduate

  • データマイニング

    2023   Weekly class   Graduate school

  • 基幹情報学特別研究1

    2023   Intensive lecture   Graduate school

  • 情報工学基礎演習1

    2023   Weekly class   Undergraduate

  • 基幹情報学特別演習I-1

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究7

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究5

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究3

    2023   Intensive lecture   Graduate school

  • 意思決定理論

    2023   Weekly class   Undergraduate

  • 計算知能

    2023   Weekly class   Undergraduate

  • 都市・地域政策

    2023   Weekly class   Graduate school

  • 先端的計算知能

    2023   Weekly class   Graduate school

  • 基幹情報学セミナー

    2023   Weekly class   Graduate school

  • 基幹情報学特別研究2

    2023   Intensive lecture   Graduate school

  • 先端ソフトウェア環境構築実践

    2023   Weekly class   Graduate school

  • 基幹情報学特別演習I-2

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究8

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究6

    2023   Intensive lecture   Graduate school

  • 基幹情報学特別研究4

    2023   Intensive lecture   Graduate school

  • 情報工学基礎演習1

    2022   Weekly class   Undergraduate

  • 情報工学特殊講義

    2022   Intensive lecture   Undergraduate

  • 工学研究の最先端

    2022   Intensive lecture   Undergraduate

  • 基幹情報学特別演習I-1

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究7

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究5

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究3

    2022   Intensive lecture   Graduate school

  • データマイニング

    2022   Weekly class   Graduate school

  • 基幹情報学特別研究1

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別演習I-2 (中百舌鳥)

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究8 (中百舌鳥)

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究6 (中百舌鳥)

    2022   Intensive lecture   Graduate school

  • 基幹情報学特別研究4 (中百舌鳥)

    2022   Intensive lecture   Graduate school

  • 先端的計算知能

    2022   Weekly class   Graduate school

  • 基幹情報学セミナー

    2022   Weekly class   Graduate school

  • 先端ソフトウェア環境構築実践

    2022   Weekly class   Graduate school

  • 計算知能

    2022   Weekly class   Undergraduate

  • 意思決定理論

    2022   Weekly class   Undergraduate

  • 電気・情報系特別研究第二

    2022   Intensive lecture   Graduate school

  • Fundamentals in Electrical and Electronic Engineering II

    2021    

  • Fundamentals in Electrical and Electronic Engineering II

    2021    

  • Advanced Intelligent Information Systems II

    2021    

  • Special Topics in Computer Science

    2021    

  • Fundamentals in Electrical and Electronic Engineering I

    2021    

  • Decision Making Theory

    2021    

  • Advanced Intelligent Information Systems I

    2021    

  • Advanced Computational Intelligence

    2021    

  • Computational Intelligence

    2021    

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Social Activities ⇒ Link to the list of Social Activities

  • A Sandbox for Teaching and Learning in CI for Pre-University and Undergraduate Students

    Role(s): Lecturer

    2023 IEEE R10 EAC & CIS  2023.03

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    Audience: High school students, University students

Visiting Lectures ⇒ Link to the list of Visiting Lectures

  • 遺伝的ファジィシステムによるデータマイニング

    Category:Engineering (machinery, electronics / physics, electrical / electronics, electrical information, chemical biotechnology, architecture, cities (civil engineering / environment), material chemistry, aerospace, marine systems, applied chemistry, chemistry, materials)

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    Keyword:データマイニング,ファジィ集合,進化計算 

    数値データから知識を獲得する方法として,遺伝的ファジィシステムが研究されている.本講義では,ファジィルール集合による知識の表現方法から,知識の精度と複雑性に関して解説する.

Job title

  • Job title within the department

    School of Engineering Department of Information Science 

    学科長  2024.04