Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 1993.06a
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- Pages.802-805
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- 1993
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
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.
Keywords