Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Structure Optimization of Fuzzy Neural Network by Genetic Algorithm

  • Fukuda, Toshio (Department of Mechano-Informatics and Systems, Nagoya University) ;
  • Ishigame, Hideyuki (Department of Mechano-Informatics and Systems, Nagoya University) ;
  • Shibata, Takanori (Department of Mechano-Informatics and Systems, Nagoya University) ;
  • Arai, Fumihito (Department of Mechano-Informatics and Systems, Nagoya University)
  • Published : 1993.06.01
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Abstract

This paper presents an auto tuning method of fuzzy inference using Genetic Algorithm. The determination of membership functions by human experts is a difficult problem. Therefore, some auto-tuning methods have been proposed to reduce the time-consuming operations. However, the convergence of the tuning by the previous methods depends on the initial conditions of the fuzzy model. So, we proposes an auto tuning method for the fuzzy neural network by Genetic Algorithm (ATF system). This paper shows effectiveness of the ATF system by simulations.

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