제어로봇시스템학회:학술대회논문집
- 2000.10a
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- Pages.370-370
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- 2000
Identification of Multi-Fuzzy Model by means of HCM Clustering and Genetic Algorithms
HCM 클러스터링과 유전자 알고리즘을 이용한 다중 퍼지 모델 동정
Abstract
In this paper, we design a Multi-Fuzzy model by means of HCM clustering 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 ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] 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.