- CSB - MetaPress - Google - Bing - Yahoo
 | 2013 | |
|---|---|---|
| j44 |      | Michela Fazzolari, Rafael Alcalá, Yusuke Nojima, Hisao Ishibuchi, Francisco Herrera: A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions. IEEE T. Fuzzy Systems 21(1): 45-65 (2013) |
| j43 | | Hisao Ishibuchi, Shingo Mihara, Yusuke Nojima: Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation. IEEE T. Fuzzy Systems 21(2): 355-368 (2013) |
| c142 | | Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima: Difficulty in Evolutionary Multiobjective Optimization of Discrete Objective Functions with Different Granularities. EMO 2013: 230-245 |
| c141 | | Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima: Relation between Neighborhood Size and MOEA/D Performance on Many-Objective Problems. EMO 2013: 459-474 |
| 2012 | ||
| c140 | | Hisao Ishibuchi, Koichiro Hoshino, Yusuke Nojima: Strategy evolution in a spatial IPD game where each agent is not allowed to play against itself. IEEE Congress on Evolutionary Computation 2012: 1-8 |
| c139 | | Hisao Ishibuchi, Koichiro Hoshino, Yusuke Nojima: Evolution of strategies in a spatial IPD game with a number of different representation schemes. IEEE Congress on Evolutionary Computation 2012: 1-8 |
| c138 | | Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi: Application of parallel distributed genetics-based machine learning to imbalanced data sets. FUZZ-IEEE 2012: 1-6 |
| c137 | | Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima: Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms. GECCO 2012: 481-488 |
| c136 | | Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima: Recombination of Similar Parents in SMS-EMOA on Many-Objective 0/1 Knapsack Problems. PPSN (2) 2012: 132-142 |
| c135 | | Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima: Ensemble Fuzzy Rule-Based Classifier Design by Parallel Distributed Fuzzy GBML Algorithms. SEAL 2012: 93-103 |
| e1 | | Lam Thu Bui, Yew-Soon Ong, Nguyen Xuan Hoai, Hisao Ishibuchi, Ponnuthurai Nagaratnam Suganthan (Eds.): Simulated Evolution and Learning - 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19, 2012. Proceedings. Lecture Notes in Computer Science 7673, Springer 2012, isbn 978-3-642-34858-7 |
| 2011 | ||
| j42 | | Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima: Design of Linguistically Interpretable Fuzzy Rule-Based Classifiers: A Short Review and Open Questions. Multiple-Valued Logic and Soft Computing 17(2-3): 101-134 (2011) |
| j41 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization. Soft Comput. 15(9): 1749-1767 (2011) |
| j40 | | Yusuke Nojima, Rafael Alcalá, Hisao Ishibuchi, Francisco Herrera: Special issue on evolutionary fuzzy systems. Soft Comput. 15(12): 2299-2301 (2011) |
| j39 | | Rafael Alcalá, Yusuke Nojima, Francisco Herrera, Hisao Ishibuchi: Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions. Soft Comput. 15(12): 2303-2318 (2011) |
| j38 | | Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima: Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. Soft Comput. 15(12): 2415-2434 (2011) |
| j37 | | Hisao Ishibuchi, Hajime Ohyanagi, Yusuke Nojima: Evolution of Strategies With Different Representation Schemes in a Spatial Iterated Prisoner's Dilemma Game. IEEE Trans. Comput. Intellig. and AI in Games 3(1): 67-82 (2011) |
| c134 | | Hisao Ishibuchi, Naoya Akedo, Hiroyuki Ohyanagi, Yusuke Nojima: Behavior of EMO algorithms on many-objective optimization problems with correlated objectives. IEEE Congress on Evolutionary Computation 2011: 1465-1472 |
| c133 | | Hisao Ishibuchi, Keisuke Takahashi, Kouichirou Hoshino, Junpei Maeda, Yusuke Nojima: Effects of configuration of agents with different strategy representations on the evolution of cooperative behavior in a spatial IPD game. CIG 2011: 313-320 |
| c132 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Hiroyuki Ohyanagi, Yusuke Nojima: Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D. EMO 2011: 166-181 |
| c131 | | Yusuke Nojima, Shinya Nishikawa, Hisao Ishibuchi: A meta-fuzzy classifier for specifying appropriate fuzzy partitions by genetic fuzzy rule selection with data complexity measures. FUZZ-IEEE 2011: 264-271 |
| c130 | | Hisao Ishibuchi, Yusuke Nojima: Toward quantitative definition of explanation ability of fuzzy rule-based classifiers. FUZZ-IEEE 2011: 549-556 |
| c129 | | Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima: A many-objective test problem for visually examining diversity maintenance behavior in a decision space. GECCO 2011: 649-656 |
| c128 | | Yusuke Nojima, Hisao Ishibuchi: Mobile Robot Controller Design by Evolutionary Multiobjective Optimization in Multiagent Environments. ICIRA (2) 2011: 515-524 |
| c127 | | Hisao Ishibuchi, Shingo Mihara, Yusuke Nojima: Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning. ICMLA (1) 2011: 229-234 |
| 2010 | ||
| j36 | | Hisao Ishibuchi: IEEE CIS VP-Technical Activities Vision Statement [Society Briefs]. IEEE Comp. Int. Mag. 5(2): 6 (2010) |
| j35 | | Ke Tang, Kay Chen Tan, Hisao Ishibuchi: Guest editorial: Memetic Algorithms for Evolutionary Multi-Objective Optimization. Memetic Computing 2(1): 1 (2010) |
| j34 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Diversity Improvement by Non-Geometric Binary Crossover in Evolutionary Multiobjective Optimization. IEEE Trans. Evolutionary Computation 14(6): 985-998 (2010) |
| c126 | | Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi: Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets. IEEE Congress on Evolutionary Computation 2010: 1-8 |
| c125 | | Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima: Effects of fine fuzzy partitions on the generalization ability of evolutionary multi-objective fuzzy rule-based classifiers. FUZZ-IEEE 2010: 1-8 |
| c124 | | Yusuke Nojima, Yutaka Kaisho, Hisao Ishibuchi: Accuracy improvement of genetic fuzzy rule selection with candidate rule addition and membership tuning. FUZZ-IEEE 2010: 1-8 |
| c123 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Simultaneous use of different scalarizing functions in MOEA/D. GECCO 2010: 519-526 |
| c122 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima: Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions. GECCO 2010: 527-534 |
| c121 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nakashima, Yusuke Nojima: Multiobjectivization from two objectives to four objectives in evolutionary multi-objective optimization algorithms. NaBIC 2010: 502-507 |
| c120 | | Shinya Nishikawa, Yusuke Nojima, Hisao Ishibuchi: Appropriate granularity specification for fuzzy classifier design by data complexity measures. NaBIC 2010: 691-696 |
| c119 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima: Many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space. PPSN (2) 2010: 91-100 |
| c118 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yoshihiko Wakamatsu, Yusuke Nojima: How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms. PPSN (1) 2010: 516-525 |
| c117 | | Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi: Parallel Distributed Implementation of Genetics-Based Machine Learning for Fuzzy Classifier Design. SEAL 2010: 309-318 |
| 2009 | ||
| j33 | | Yusuke Nojima, Hisao Ishibuchi, Isao Kuwajima: Parallel distributed genetic fuzzy rule selection. Soft Comput. 13(5): 511-519 (2009) |
| j32 | | Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi: Special issue on emerging trends in soft computing: memetic algorithms. Soft Comput. 13(8-9): 739-740 (2009) |
| j31 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima: Use of biased neighborhood structures in multiobjective memetic algorithms. Soft Comput. 13(8-9): 795-810 (2009) |
| c116 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima: Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 530-537 |
| c115 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Effects of using two neighborhood structures on the performance of cellular evolutionary algorithms for many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 2508-2515 |
| c114 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Adaptation of Scalarizing Functions in MOEA/D: An Adaptive Scalarizing Function-Based Multiobjective Evolutionary Algorithm. EMO 2009: 438-452 |
| c113 | | Hisao Ishibuchi, Yusuke Nojima: Discussions on Interpretability of Fuzzy Systems using Simple Examples. IFSA/EUSFLAT Conf. 2009: 1649-1654 |
| c112 | | Yusuke Nojima, Hisao Ishibuchi: Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference. IFSA/EUSFLAT Conf. 2009: 1839-1844 |
| c111 | | Hisao Ishibuchi, Hiroyuki Ohyanagi, Yusuke Nojima: Evolution of cooperative behavior in a spatial iterated prisoner's dilemma game with different representation schemes of game strategies. FUZZ-IEEE 2009: 1568-1573 |
| c110 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach. FUZZ-IEEE 2009: 1609-1614 |
| c109 | | Rafael Alcalá, Yusuke Nojima, Francisco Herrera, Hisao Ishibuchi: Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection. FUZZ-IEEE 2009: 1718-1723 |
| c108 | | Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima: Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. FUZZ-IEEE 2009: 1724-1729 |
| c107 | | Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima: Complexity, interpretability and explanation capability of fuzzy rule-based classifiers. FUZZ-IEEE 2009: 1730-1735 |
| c106 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Single-objective and multi-objective formulations of solution selection for hypervolume maximization. GECCO 2009: 1831-1832 |
| c105 | | Yusuke Nojima, Hisao Ishibuchi: Effects of Data Reduction on the Generalization Ability of Parallel Distributed Genetic Fuzzy Rule Selection. ISDA 2009: 96-101 |
| c104 | | Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima: Evolutionary Many-Objective Optimization by NSGA-II and MOEA/D with Large Populations. SMC 2009: 1758-1763 |
| c103 | | Yusuke Nojima, Yusuke Nakashima, Hisao Ishibuchi: Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning. SoCPaR 2009: 341-346 |
| c102 | | Yuki Tsujimoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima, Hisao Ishibuchi: Effects of Including Single-Objective Optimal Solutions in an Initial Population on Evolutionary Multiobjective Optimization. SoCPaR 2009: 352-357 |
| c101 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Empirical Analysis of Using Weighted Sum Fitness Functions in NSGA-II for Many-Objective 0/1 Knapsack Problems. UKSim 2009: 71-76 |
| p8 | | Gerald Schaefer, Tomoharu Nakashima, Hisao Ishibuchi: Gene Expression Analysis by Fuzzy and Hybrid Fuzzy Classification. Fuzzy Systems in Bioinformatics and Computational Biology 2009: 127-140 |
| 2008 | ||
| j30 | | Hisao Ishibuchi, Kaname Narukawa, Noritaka Tsukamoto, Yusuke Nojima: An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization. European Journal of Operational Research 188(1): 57-75 (2008) |
| c100 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Evolutionary many-objective optimization: A short review. IEEE Congress on Evolutionary Computation 2008: 2419-2426 |
| c99 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima: Scalability of multiobjective genetic local search to many-objective problems: Knapsack problem case studies. IEEE Congress on Evolutionary Computation 2008: 3586-3593 |
| c98 | | Seiya Fujii, Tomoharu Nakashima, Hisao Ishibuchi: A study on constructing fuzzy systems for high-level decision making in a car racing game. IEEE Congress on Evolutionary Computation 2008: 3626-3633 |
| c97 | | El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, Günter Rudolph, Carlos A. Coello Coello: Parallel Approaches for Multiobjective Optimization. Multiobjective Optimization 2008: 349-372 |
| c96 | | Isao Kuwajima, Hisao Ishibuchi, Yusuke Nojima: Effectiveness of designing fuzzy rule-based classifiers from Pareto-optimal rules. FUZZ-IEEE 2008: 1185-1192 |
| c95 | | Seiya Fujii, Tomoharu Nakashima, Hisao Ishibuchi: A study on constructing fuzzy systems for high-level decision making in a car racing game. FUZZ-IEEE 2008: 2299-2306 |
| c94 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima: Effectiveness of scalability improvement attempts on the performance of NSGA-II for many-objective problems. GECCO 2008: 649-656 |
| c93 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Maintaining the diversity of solutions by non-geometric binary crossover: a worst one-max solver competition case study. GECCO 2008: 1111-1112 |
| c92 | | Yusuke Nojima, Hisao Ishibuchi: Effects of Diversity Measures on the Design of Ensemble Classifiers by Multiobjective Genetic Fuzzy Rule Selection with a Multi-classifier Coding Scheme. HAIS 2008: 755-763 |
| c91 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures. PPSN 2008: 458-467 |
| c90 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima: Use of Heuristic Local Search for Single-Objective Optimization in Multiobjective Memetic Algorithms. PPSN 2008: 743-752 |
| c89 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures. SEAL 2008: 309-318 |
| c88 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Behavior of Evolutionary Many-Objective Optimization. UKSim 2008: 266-271 |
| c87 | | Hisao Ishibuchi: Evolutionary multiobjective optimization and multiobjective fuzzy system design. CSTST 2008: 3-4 |
| p7 | | Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima: Evolutionary Multi-objective Rule Selection for Classification Rule Mining. Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases 2008: 47-70 |
| p6 | | Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima: Evolutionary Multiobjective Design of Fuzzy Rule-Based Classifiers. Computational Intelligence: A Compendium 2008: 641-685 |
| p5 | | Hisao Ishibuchi, Yusuke Nojima: Pattern Classification with Linguistic Rules. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 2008: 377-395 |
| 2007 | ||
| j29 | | Tomoharu Nakashima, Gerald Schaefer, Yasuyuki Yokota, Hisao Ishibuchi: A weighted fuzzy classifier and its application to image processing tasks. Fuzzy Sets and Systems 158(3): 284-294 (2007) |
| j28 | | Hisao Ishibuchi, Yusuke Nojima: Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning. Int. J. Approx. Reasoning 44(1): 4-31 (2007) |
| j27 | | Yusuke Nojima, Hisao Ishibuchi: Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design. Int. J. Hybrid Intell. Syst. 4(3): 157-169 (2007) |
| j26 | | Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer, Ales Drastich, Michal Zavisek: Constructing Cost-Sensitive Fuzzy-Rule-Based Systems for Pattern Classification Problems. JACIII 11(6): 546-553 (2007) |
| j25 | | Yew-Soon Ong, Natalio Krasnogor, Hisao Ishibuchi: Special Issue on Memetic Algorithms. IEEE Transactions on Systems, Man, and Cybernetics, Part B 37(1): 2-5 (2007) |
| c86 | | Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima: An empirical study on the specification of the local search application probability in multiobjective memetic algorithms. IEEE Congress on Evolutionary Computation 2007: 2788-2795 |
| c85 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Iterative approach to indicator-based multiobjective optimization. IEEE Congress on Evolutionary Computation 2007: 3967-3974 |
| c84 | | Ken Ohara, Yusuke Nojima, Yumeka Kitano, Hisao Ishibuchi: Effects of spatial structures on evolution of iterated prisoner's dilemma game strategies with probabilistic decision making. IEEE Congress on Evolutionary Computation 2007: 4051-4058 |
| c83 | | Gerald Schaefer, Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi: Cost-Sensitive Fuzzy Classification for Medical Diagnosis. CIBCB 2007: 312-316 |
| c82 | | |
| c81 | | Hisao Ishibuchi: Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions. FUZZ-IEEE 2007: 1-6 |
| c80 | | Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi: Introducing Class-Based Classification Priority in Fuzzy Rule-Based Classification Systems. FUZZ-IEEE 2007: 1-6 |
| c79 | | Yusuke Nojima, Isao Kuwajima, Hisao Ishibuchi: Data Set Subdivision for Parallel Distributed Implementation of Genetic Fuzzy Rule Selection. FUZZ-IEEE 2007: 1-6 |
| c78 | | Gerald Schaefer, Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi: Fuzzy Classification of Gene Expression Data. FUZZ-IEEE 2007: 1-6 |
| c77 | | Gerald Schaefer, Tomoharu Nakashima, Michal Zavisek, Yasuyuki Yokota, Ales Drastich, Hisao Ishibuchi: Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms. FUZZ-IEEE 2007: 1-5 |
| c76 | | Hisao Ishibuchi, Yusuke Nojima, Noritaka Tsukamoto, Ken Ohara: Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization. GECCO 2007: 829-836 |
| c75 | | Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima: Prescreening of Candidate Rules Using Association Rule Mining and Pareto-optimality in Genetic Rule Selection. KES (2) 2007: 509-516 |
| c74 | | Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima: Choosing extreme parents for diversity improvement in evolutionary multiobjective optimization algorithms. SMC 2007: 1946-1951 |
| p4 | | Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima: Use of Pareto-Optimal and Near Pareto-Optimal Candidate Rules in Genetic Fuzzy Rule Selection. Analysis and Design of Intelligent Systems using Soft Computing Techniques 2007: 387-396 |
| 2006 | ||
| j24 | | Hisao Ishibuchi, Yusuke Nojima: Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers. Int. J. Hybrid Intell. Syst. 3(3): 129-145 (2006) |
| j23 | | Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima: An approach to fuzzy default reasoning for function approximation. Soft Comput. 10(9): 850-864 (2006) |
| c73 | | Tomoharu Nakashima, Hisao Ishibuchi, Masahiro Takatani, Manabu Nii: The Effect of Using Match History on the Evolution of RoboCup Soccer Team Strategies. CIG 2006: 60-66 |
| c72 | | Hisao Ishibuchi, Yusuke Nojima: Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization. EMO 2006: 51-65 |
| c71 | | Hisao Ishibuchi, Yusuke Nojima, Kaname Narukawa, Tsutomu Doi: Incorporation of decision maker's preference into evolutionary multiobjective optimization algorithms. GECCO 2006: 741-742 |
| c70 | | Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima: Multiobjective genetic rule selection as a data mining postprocessing procedure. GECCO 2006: 1591-1592 |
| c69 | | Yusuke Nojima, Hisao Ishibuchi: Designing Fuzzy Ensemble Classifiers by Evolutionary Multiobjective Optimization with an Entropy-Based Diversity Criterion. HIS 2006: 59 |
| c68 | | Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima: Finding Simple Fuzzy Classification Systems with High Interpretability Through Multiobjective Rule Selection. KES (2) 2006: 86-93 |
| c67 | | Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima: Incorporation of Scalarizing Fitness Functions into Evolutionary Multiobjective Optimization Algorithms. PPSN 2006: 493-502 |
| c66 | | Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima: Effects of Using Two Neighborhood Structures in Cellular Genetic Algorithms for Function Optimization. PPSN 2006: 949-958 |
| c65 | | Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi: Examining the Effect of Cost Assignment on the Performance of Cost-Based Classification Systems. SMC 2006: 2772-2777 |
| p3 | | Hisao Ishibuchi, Yusuke Nojima: Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection. Multi-Objective Machine Learning 2006: 507-530 |
| 2005 | ||
| j22 | | Hisao Ishibuchi, Naoki Namikawa: Evolution of iterated prisoner's dilemma game strategies in structured demes under random pairing in game playing. IEEE Trans. Evolutionary Computation 9(6): 552-561 (2005) |
| j21 | | Hisao Ishibuchi, Takashi Yamamoto: Rule Weight Specification in Fuzzy Rule-Based Classification Systems. IEEE T. Fuzzy Systems 13(4): 428-435 (2005) |
| j20 | | Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima: Hybridization of fuzzy GBML approaches for pattern classification problems. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(2): 359-365 (2005) |
| c64 |  | Satoshi Yokoyama, Naoki Namikawa, Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi: Developing a Goal Keeper for Simulated RoboCup Soccer and its Performance Evaluation. AMiRE 2005: 75-80 |
| c63 | | Hisao Ishibuchi, Naoki Namikawa: Evolution of cooperative behavior in the iterated prisoner's dilemma under random pairing in game playing. Congress on Evolutionary Computation 2005: 2637-2644 |
| c62 | | Hisao Ishibuchi: Effects of Crossover Operations on the Performance of EMO Algorithms. Practical Approaches to Multi-Objective Optimization 2005 |
| c61 | | Hisao Ishibuchi, Kaname Narukawa: Recombination of Similar Parents in EMO Algorithms. EMO 2005: 265-279 |
| c60 | | Yusuke Nojima, Kaname Narukawa, Shiori Kaige, Hisao Ishibuchi: Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm. EMO 2005: 341-354 |
| c59 | | Hisao Ishibuchi, Shiori Kaige, Kaname Narukawa: Comparison Between Lamarckian and Baldwinian Repair on Multiobjective 0/1 Knapsack Problems. EMO 2005: 370-385 |
| c58 | | Hisao Ishibuchi, Yusuke Nojima: Multiobjective Formulations of Fuzzy Rule-Based Classification System Design. EUSFLAT Conf. 2005: 285-290 |
| c57 | | Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer: Learning Fuzzy If-Then Rules for Pattern Classi cation with Weighted Training Patterns. EUSFLAT Conf. 2005: 1064-1069 |
| c56 | | Hisao Ishibuchi, Kaname Narukawa: Comparison of evolutionary multiobjective optimization with rference solution-based single-objective approach. GECCO 2005: 787-794 |
| c55 | | Hisao Ishibuchi, Kaname Narukawa, Yusuke Nojima: An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization. GECCO 2005: 817-824 |
| c54 | | Hisao Ishibuchi, Kaname Narukawa: Spatial Implementation of Evolutionary Multiobjective Algorithms with Partial Lamarckian Repair for Multiobjective Knapsack Problems. HIS 2005: 265-270 |
| c53 | | Hisao Ishibuchi, Yusuke Nojima: Performance Evaluation of Evolutionary Multiobjective Approaches to the Design of Fuzzy Rule-Based Ensemble Classifiers. HIS 2005: 271-276 |
| c52 | | Tomoharu Nakashima, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi, Manabu Nii: Performance Evaluation of an Evolutionary Method for RoboCup Soccer Strategies. RoboCup 2005: 616-623 |
| c51 | | Hiroko Kitano, Tomoharu Nakashima, Hisao Ishibuchi: Behavior Analysis of Futures Trading Agents Using Fuzzy Rule Extraction. SMC 2005: 1477-1481 |
| p2 | | Tomoharu Nakashima, Hisao Ishibuchi: Using Boosting Techniques to Improve the Performance of Fuzzy Classification Systems. Classification and Clustering for Knowledge Discovery 2005: 147-157 |
| p1 | | Tomoharu Nakashima, Takanobu Ariyama, Hiroko Kitano, Hisao Ishibuchi: A Fuzzy Rule-Based Trading Agent: Analysis and Knowledge Extraction. Computational Intelligence for Modelling and Prediction 2005: 265-277 |
| 2004 | ||
| j19 | | Hisao Ishibuchi, Takashi Yamamoto: Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. Fuzzy Sets and Systems 141(1): 59-88 (2004) |
| j18 | | Hisao Ishibuchi: Book Review: "Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases" by Oscar Cordon, Francisco Herrera, Frank Hoffmann and Luis Magdalena; World Scientific, Singapore, New Jersey, London, Hong Kong, 2001, 462pp., ISBN 981-02-4016-3. Fuzzy Sets and Systems 141(1): 161-162 (2004) |
| j17 | | Hisao Ishibuchi, Shiori Kaige: Implementation of Simple Multiobjective Memetic Algorithms and Its Applications to Knapsack Problems. Int. J. Hybrid Intell. Syst. 1(1): 22-35 (2004) |
| c50 | | Hisao Ishibuchi, Kaname Narukawa: Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization. GECCO (1) 2004: 1246-1258 |
| c49 | | Hisao Ishibuchi, Youhei Shibata: Mating Scheme for Controlling the Diversity-Convergence Balance for Multiobjective Optimization. GECCO (1) 2004: 1259-1271 |
| c48 | | Hisao Ishibuchi, Kaname Narukawa: Comparison of Local Search Implementation Schemes in Hybrid Evolutionary Multiobjective Optimization Algorithms. HIS 2004: 404-409 |
| c47 | | Tomoharu Nakashima, Hisao Ishibuchi, Andrzej Bargiela: A Study on Weighting Training Patterns for Fuzzy Rule-Based Classification Systems. MDAI 2004: 60-69 |
| c46 | | Hisao Ishibuchi, Satoshi Namba: Evolutionary Multiobjective Knowledge Extraction for High-Dimensional Pattern Classification Problems. PPSN 2004: 1123-1132 |
| c45 | | Tomoharu Nakashima, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi: An evolutionary approach for strategy learning in RoboCup soccer. SMC (2) 2004: 2023-2028 |
| c44 | | Tomoharu Nakashima, Hiroko Kitano, Hisao Ishibuchi: Development of a fuzzy position controller for an autonomously trading agent. SMC (3) 2004: 2338-2343 |
| c43 | | Hisao Ishibuchi, Takashi Yamamoto: Multi-objective evolutionary design of fuzzy rule-based systems. SMC (3) 2004: 2362-2367 |
| c42 | | Tomoharu Nakashima, Hisao Ishibuchi, Andrzej Bargiela: Constructing fuzzy classification systems from weighted training patterns. SMC (3) 2004: 2386-2391 |
| 2003 | ||
| j16 | | Hisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima: Learning fuzzy rules from iterative execution of games. Fuzzy Sets and Systems 135(2): 213-240 (2003) |
| j15 | | Hisao Ishibuchi, Tadashi Yoshida, Tadahiko Murata: Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Trans. Evolutionary Computation 7(2): 204-223 (2003) |
| c41 | | Hisao Ishibuchi, Youhei Shibata: An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms. EMO 2003: 433-447 |
| c40 | | Tadahiko Murata, Hiroyuki Nozawa, Hisao Ishibuchi, Mitsuo Gen: Modification of Local Search Directions for Non-dominated Solutions in CellularMultiobjective Genetic Algorithms forPattern Classification Problems. EMO 2003: 593-607 |
| c39 | | Hisao Ishibuchi, Takashi Yamamoto: Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems. EMO 2003: 608-622 |
| c38 | | Hisao Ishibuchi, Youhei Shibata: A Similarity-Based Mating Scheme for Evolutionary Multiobjective Optimization. GECCO 2003: 1065-1076 |
| c37 | | Hisao Ishibuchi, Takashi Yamamoto: Evolutionary Multiobjective Optimization for Generating an Ensemble of Fuzzy Rule-Based Classifiers. GECCO 2003: 1077-1088 |
| c36 | | Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi: Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms. GECCO 2003: 1234-1245 |
| c35 | | Hisao Ishibuchi, Shiori Kaige: A Simple but Powerful Multiobjective Hybrid Genetic Algorithm. HIS 2003: 244-251 |
| c34 | | Hisao Ishibuchi, Takashi Yamamoto: Interpretability Issues in Fuzzy Genetics-Based Machine Learning for Linguistic Modelling. Modelling with Words 2003: 209-228 |
| c33 | | Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi: A Fuzzy Reinforcement Learning for a Ball Interception Problem. RoboCup 2003: 559-567 |
| c32 | | Shiori Kaige, Tadahiko Murata, Hisao Ishibuchi: Performance evaluation of memetic EMO algorithms using dominance relation-based replacement rules on MOO test problems. SMC 2003: 14-19 |
| c31 | | Tomoham Nakashima, Gaku Nakai, Hisao Ishibuchi: Constructing fuzzy ensembles for pattern classification problems. SMC 2003: 3200-3205 |
| c30 | | Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi: Knowledge acquisition for a soccer agent by fuzzy reinforcement learning. SMC 2003: 4256-4261 |
| 2002 | ||
| c29 | | Tomoharu Nakashima, Takanobu Ariyama, Hisao Ishibuchi: On-Line Learning of a Fuzzy System for a Future Market. FSKD 2002: 54-58 |
| c28 | | Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi: A Boosting Algorithm of Fuzzy Rule-Based Systems for Pattern Classification Problems. FSKD 2002: 155-158 |
| c27 | | Hisao Ishibuchi, Takashi Yamamoto: Fuzzy Rule Selection By Data Mining Criteria And Genetic Algorithms. GECCO 2002: 399-406 |
| c26 | | Hisao Ishibuchi, Tadashi Yoshida, Tadahiko Murata: Balance Between Genetic Search And Local Search In Hybrid Evolutionary Multi-criterion Optimization Algorithms. GECCO 2002: 1301-1308 |
| c25 | | Hisao Ishibuchi, Takashi Yamamoto: Comparison of Fuzzy Rule Selection Criteria for Classification Problems. HIS 2002: 132-141 |
| c24 | | Hisao Ishibuchi, Tadashi Yoshida: Hybrid Evolutionary Multi-Objective Optimization Algorithms. HIS 2002: 163-172 |
| 2001 | ||
| j14 | | Hisao Ishibuchi, Manabu Nii: Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks. Fuzzy Sets and Systems 119(2): 273-290 (2001) |
| j13 | | Hisao Ishibuchi, Manabu Nii: Numerical analysis of the learning of fuzzified neural networks from fuzzy if-then rules. Fuzzy Sets and Systems 120(2): 281-307 (2001) |
| j12 | | Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata: Three-objective genetics-based machine learning for linguistic rule extraction. Inf. Sci. 136(1-4): 109-133 (2001) |
| j11 | | Hisao Ishibuchi, Tomoharu Nakashima, Ryoji Sakamoto: Evolution of unplanned coordination in a market selection game. IEEE Trans. Evolutionary Computation 5(5): 524-534 (2001) |
| j10 | | Hisao Ishibuchi, Tomoharu Nakashima: Effect of rule weights in fuzzy rule-based classification systems. IEEE T. Fuzzy Systems 9(4): 506-515 (2001) |
| c23 | | Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen: Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms. EMO 2001: 82-95 |
| c22 | | Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata: Multiobjective Optimization in Linguistic Rule Extraction from Numerical Data. EMO 2001: 588-602 |
| c21 | | Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima: Linguistic Modelling for Function Approximation Using Grid Partitions. FUZZ-IEEE 2001: 47-50 |
| c20 | | Hisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima: Adaption of Fuzzy Rule-Based Systems for Game Playing . FUZZ-IEEE 2001: 1448-1451 |
| c19 | | Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima: Determination of Rule Weights of Fuzzy Association Rules. FUZZ-IEEE 2001: 1555-1558 |
| c18 | | Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima: Fuzzy Data Mining: Effect of Fuzzy Discretization. ICDM 2001: 241-248 |
| 2000 | ||
| j9 | | Hisao Ishibuchi, Tomoharu Nakashima: Pattern and Feature Selection by Genetic Algorithms in Nearest Neighbor Classification. JACIII 4(2): 138-145 (2000) |
| c17 | | Hisao Ishibuchi, Tomoharu Nakashima: Linguistic Rule Extraction by Genetics-Based Machine Learning. GECCO 2000: 195-202 |
| c16 | | Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen: Cellular Genetic Local Search for Multi-Objective Optimization. GECCO 2000: 307-314 |
| c15 | | Hisao Ishibuchi, Tatsuo Nakari, Tomoharu Nakashima: Evolution of Strategies in Spatial IPD Games with Structure Demes. GECCO 2000: 817-824 |
| c14 | | Hisao Ishibuchi, Tomoharu Nakashima: Multi-objective pattern and feature selection by a genetic algorithm. GECCO 2000: 1069- |
| 1999 | ||
| j8 | | Hisao Ishibuchi, Tadahiko Murata, Tomoharu Nakashima: Linguistic Rule Extraction from Numerical Data for High-dimensional Classification Problems. JACIII 3(5): 386-393 (1999) |
| j7 | | Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata: Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems. IEEE Transactions on Systems, Man, and Cybernetics, Part B 29(5): 601-618 (1999) |
| 1998 | ||
| j6 | | Hisao Ishibuchi, Tadahiko Murata: A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Transactions on Systems, Man, and Cybernetics, Part C 28(3): 392-403 (1998) |
| c13 | | Tadahiko Murata, Hisao Ishibuchi, Tomoharu Nakashima, Mitsuo Gen: Fuzzy Partition and Input Selection by Genetic Algorithms for Designing Fuzzy Rule-Based Classification Systems. Evolutionary Programming 1998: 407-416 |
| c12 | | Hisao Ishibuchi, Tomoharu Nakashima: A study on generating fuzzy classification rules using histograms. KES (1) 1998: 132-140 |
| c11 | | Hisao Ishibuchi, Manabu Nii: Improving the generalization ability of neural networks by interval arithmetic. KES (1) 1998: 231-236 |
| c10 | | Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen: Neighborhood structures for genetic local search algorithms. KES (2) 1998: 259-263 |
| c9 | | Manabu Nii, Hisao Ishibuchi: Fuzzy arithmetic in neural networks for linguistic rule extraction. KES (2) 1998: 387-394 |
| c8 | | Hisao Ishibuchi, Tomoharu Nakashima: Evolution of Reference Sets in Nearest Neighbor Classification. SEAL 1998: 82-89 |
| c7 | | Kimiko Tanaka, Manabu Nii, Hisao Ishibuchi: Learning from Linguistic Rules and Rule Extraction for Function Approximation by Neural Networks. SEAL 1998: 317-324 |
| 1997 | ||
| c6 | | Hisao Ishibuchi, Tadahiko Murata, Shigemitsu Tomioka: Effectiveness of Genetic Local Search Algorithms. ICGA 1997: 505-512 |
| 1996 | ||
| j5 | | Ken Nozaki, Hisao Ishibuchi, Hideo Tanaka: Adaptive fuzzy rule-based classification systems. IEEE T. Fuzzy Systems 4(3): 238-250 (1996) |
| c5 | | Hisao Ishibuchi, Tadahiko Murata: Multi-Objective Genetic Local Search Algorithm. International Conference on Evolutionary Computation 1996: 119-124 |
| c4 | | Tadahiko Murata, Hisao Ishibuchi: Positive and Negative Combination Effects of Crossover and Mutation Operators in Sequencing Problems. International Conference on Evolutionary Computation 1996: 170-175 |
| c3 | | Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata: Genetic-Algorithm-Based Approaches to the Design of Fuzzy Systems for Multi-Dimensional Pattern Classification Problems. International Conference on Evolutionary Computation 1996: 229-234 |
| 1995 | ||
| j4 | | Hisao Ishibuchi: Preface: 3rd international conference on fuzzy logic, neural nets, and soft computing. Int. J. Approx. Reasoning 13(4): 247-248 (1995) |
| j3 | | Hisao Ishibuchi, Kouichi Morioka, I. Burhan Türksen: Learning by fuzzified neural networks. Int. J. Approx. Reasoning 13(4): 327-358 (1995) |
| c2 | | Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata: A Fuzzy Classifier System That Generates Linguistic Rules for Pattern Classification Problems. IEEE/Nagoya-University World Wisepersons Workshop 1995: 35-54 |
| 1994 | ||
| j2 | | Hisao Ishibuchi, Hideo Tanaka, Hidehiko Okada: Interpolation of fuzzy if-then rules by neural networks. Int. J. Approx. Reasoning 10(1): 3-27 (1994) |
| c1 | | Tadahiko Murata, Hisao Ishibuchi: Performance Evaluation of Genetic Algorithms for Flowshop Scheduling Problems. International Conference on Evolutionary Computation 1994: 812-817 |
| 1993 | ||
| j1 | | Hideo Tanaka, Hisao Ishibuchi: Evidence theory of exponential possibility distributions. Int. J. Approx. Reasoning 8(2): 123-140 (1993) |
Colors in the list of coauthors
Last update Sun May 19 16:20:42 2013 CET by the DBLP Team —
Data released under the ODC-BY 1.0 license — See also our legal information page