Design of IG-based Fuzzy Models Using Improved Space Search Algorithm
개선된 공간 탐색 알고리즘을 이용한 정보입자 기반 퍼지모델 설계

Sung-Kwun Oh, Hyun-Ki Kim
2011 Journal of Korean institute of intelligent systems  
This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information
more » ... granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.
doi:10.5391/jkiis.2011.21.6.686 fatcat:ehineioxjneu5mhgst7ggyawqy