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

Korean Institute of Intelligent Systems (한국지능시스템학회)
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GMDH by Fuzzy If-Then Rules with Certainty Factors

  • M.Balazinski (Department of Industrial Engineering, University of Osaka Prefecture) ;
  • Katsunori-Yokode (Department of Industrial Engineering, University of Osaka Prefecture) ;
  • Hisao-Ishibuchi (Department of Industrial Engineering, University of Osaka Prefecture)
  • Published : 1993.06.01
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Abstract

A method of automatic learning of fuzzy if-then rules with certainty factors from the given input-output data is developed. A certainty factor expresses the degree to which a fuzzy if-then rule is fitting to the given data. Fuzzy if-then rules with certainty factors are generated without optimization techniques. The obtained fuzzy if-then rules can be regarded as an approximator of a non-linear function. This method is applied to GMDH (Group Method of Data Handling) to cope with difficulty in approximating multi-input functions with fuzzy if-then rules.

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