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

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Automatic Generation of Fuzzy Rules using the Fuzzy-Neural Networks

  • Ahn, Taechon (Dept. of Control & InstrumentationEngineering, Wonkang Univ.) ;
  • Oh, Sungkwun (Dept. of Electrical Engineering, Yonsei Univ.) ;
  • Woo, Kwangbang (Dept. of Electrical Engineering, Yonsei Univ.)
  • Published : 1993.06.01
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Abstract

In the paper, a new design method of rule-based fuzzy modeling is proposed for model identification of nonlinear systems. The structure indentification is carried out, utilizing fuzzy c-means clustering. Fuzzy-neural networks composed back-propagation algorithm and linear fuzzy inference method, are used to identify parameters of the premise and consequence parts. To obtain optimal linguistic fuzzy implication rules, the learning rates and momentum coefficients are tuned automatically using a modified complex method.

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