Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.07d
- /
- Pages.3007-3009
- /
- 2000
The Identification of Multi-Fuzzy Model by means of HCM and Genetic Algorithms
클러스터링 기법과 유전자 알고리즘에 의한 다중 퍼지 모델으 동정
- Park, Byoun-Jun (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
- Lee, Su-Gu (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
- Oh, Sung-Kwun (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
- Kim, Hyun-Ki (School of Electrical Engineering, Suwon Univ.)
- Published : 2000.07.17
Abstract
In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.
Keywords