International Journal of Control, Automation, and Systems

  • 제5권4호
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  • Pages.444-455
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  • 2007
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  • 1598-6446(pISSN)
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  • 2005-4092(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
권호 표지

On Generating Fuzzy Systems based on Pareto Multi-objective Cooperative Coevolutionary Algorithm

  • Xing, Zong-Yi (School of Mechanical Engineering/Automation, Nanjing University of Science and Technology) ;
  • Zhang, Yong (School of Mechanical Engineering/Automation, Nanjing University of Science and Technology) ;
  • Hou, Yuan-Long (School of Mechanical Engineering/Automation, Nanjing University of Science and Technology) ;
  • Jia, Li-Min (School of Traffic and Transportation, Beijing Jiaotong University)
  • 발행 : 2007.08.31
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초록

An approach to construct multiple interpretable and precise fuzzy systems based on the Pareto Multi-objective Cooperative Coevolutionary Algorithm (PMOCCA) is proposed in this paper. First, a modified fuzzy clustering algorithm is used to construct antecedents of fuzzy system, and consequents are identified separately to reduce computational burden. Then, the PMOCCA and the interpretability-driven simplification techniques are executed to optimize the initial fuzzy system with three objectives: the precision performance, the number of fuzzy rules and the number of fuzzy sets; thus both the precision and the interpretability of the fuzzy systems are improved. In order to select the best individuals from each species, we generalize the NSGA-II algorithm from one species to multi-species, and propose a new non-dominated sorting technique and collaboration mechanism for cooperative coevolutionary algorithm. Finally, the proposed approach is applied to two benchmark problems, and the results show its validity.

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