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

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Tuning Fuzzy Rules Based on Additive-Type Fuzzy System Models

  • Shi, Yan (School of Engineering , Kyushu Tokai University) ;
  • Mizumoto, Masaharu (Division of Information and Computer Sciences, Osaka Electro-Communication University)
  • Published : 1998.06.01
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Abstract

In this paper, we suggested a neuro-fuzzy learning algorithm for tuning fuzzy rules, in which a fuzzy system model is of additive-type. Using the method, it is possible to reduce the computation size, since performing the fuzzy inference and tuning the fuzzy rules of each fuzzy subsystem model are independent. Moreover, the efficiency of suggested method is shown by means of a numerical example.

Keywords