標題: A Novel Self-Constructing Evolution Algorithm for TSK-type Fuzzy Model Design
作者: Lin, Sheng-Fuu
Chang, Jyun-Wei
Cheng, Yi-Chang
Hsu, Yung-Chi
電機工程學系
Department of Electrical and Computer Engineering
公開日期: 2010
摘要: In this paper, a novel self-constructing evolution algorithm (SCEA) for TSK-type fuzzy model (TFM) design is proposed. The proposed SCEA method is different from the traditional genetic algorithms (GA). A chromosome of the population in GA represents a full solution and only one population presents all solutions. Our method applies a population to evaluate a partial solution locally, and several populations to construct the full solution. Thus, a chromosome represents only partial solution. The proposed SCEA uses the self-constructing learning algorithm to construct the TFM automatically that is based on the input data to decide the input partition. And we also adopted the sequence search-based dynamic evolution (SSDE) method to perform parameter learning. Simulation results have shown that the proposed SCEA method obtains better performance than some existing models.
URI: http://hdl.handle.net/11536/25987
ISBN: 978-1-4244-8126-2
期刊: 2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Appears in Collections:Conferences Paper