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

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Rule Merging Method for Fuzzy Classifier Systems and Its Applications to Fuzzy Control Rules Acquisition

  • Inoue, Hiroyuki (Faculty of Education and Regional Studies, Fukui University) ;
  • Kamei, Katsuari (Faculty of Science and Engineering, Ritsumeikan University)
  • Published : 2003.09.01
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Abstract

This paper proposes a fuzzy classifier system (FCS) using hyper-cone membership functions (HCMFs) and rule reduction techniques. The FCS can generate excellent rules which have the best number of rules and the best location and shape of membership functions. The HCMF is expressed by a kind of radial basis function, and its fuzzy rule can be flexibly located in input and output spaces. The rule reduction technique adopts a decreasing method by merging the two appropriate rules. We applay the FCS to a tubby rule generation for the inverted pendulum control.

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