Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.07d
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- Pages.2305-2307
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- 2000
Neuro-Fuzzy Modeling of Complex Nonlinear System Using a mGA
mGA를 사용한 복잡한 비선형 시스템의 뉴로-퍼지 모델링
- Choi, Jong-Il (Dept. of Electronics & Info. Eng. Kunsan Univ.) ;
- Lee, Yeun-Woo (Dept. of Electronics & Info. Eng. Kunsan Univ.) ;
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Joo, Young-Hoon
(Dept. of Electronics & Info. Eng. Kunsan Univ.) ;
- Park, Jin-Bae (Dept. of Electric & Computer Eng. Yonsei Univ.)
- Published : 2000.07.17
Abstract
In this paper we propose a Neuro-Fuzzy modeling method using mGA for complex nonlinear system. mGA has more effective and adaptive structure than sGA with respect to using the changeable-length string. This paper suggest a new coding method for applying the model's input and output data to the number of optimul rules of fuzzy models and the structure and parameter identifications of membership function simultaneously. The proposed method realize optimal fuzzy inference system using the learning ability of Neural network. For fine-tune of the identified parameter by mGA, back-propagation algorithm used for optimulize the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through compare with ANFIS.
Keywords