Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2001.07d
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- Pages.1952-1954
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- 2001
Neuro-Fuzzy Modeling for Nonlinear System Using VmGA
VmGA를 이용한 비선형 시스템의 뉴로-퍼지 모델링
- Choi, Jong-Il (School of Electronic & Information. Eng. Kunsan Univ.) ;
- Lee, Yeun-Woo (School of Electronic & Information. Eng. Kunsan Univ.) ;
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Joo, Young-Hoon
(School of Electronic & Information. Eng. Kunsan Univ.) ;
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Park, Jin-Bae
(Dept. of Electrical & Electronic Eng.)
- Published : 2001.07.18
Abstract
In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing 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 comparing with ANFIS.
Keywords