Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1996.07b
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- Pages.1009-1011
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- 1996
Automatic Fuzzy Model Identification Using Genetic Algorithm
유전 알고리듬을 이용한 퍼지모델의 자동 동정
- Son, You-Seck (Dept. of Electrical Engineering. Yonsei Univ.) ;
- Chnng, Wook (Dept. of Electrical Engineering. Yonsei Univ.) ;
- Park, Jin-Bae (Dept. of Electrical Engineering. Yonsei Univ.) ;
- Joo, Young-Hoon (Dept. of Control & Instrumentation Engineering, Kunsan Univ.)
- Published : 1996.07.22
Abstract
This paper presents an approach to building multi-input and single-output fuzzy models for nonlinear data-based systems. Such a model is composed of fuzzy rules, and its output is inferred by simplified reasoning. Optimal structure and membership parameters for a fuzzy model are automatically and simultaneously identified by GA(Genetic Algorithm). Numerical examples are provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce a fuzzy model with higher accuracy and a smaller number of fuzzy rules than the ones achieved previously in other methods.
Keywords