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ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm
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[1]ZHU Xiao-dong,LIU Dan,Ll Guang.ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2015,36(04):10-14.[doi:10.3969/ j. issn.1671 -6833.2015.04.003]
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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 36卷 Number of periods: 2015 04 Page number: 10-14 Column: Public date: 2015-08-31
Title:
ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm
Author(s):
ZHU Xiao-dong; LIU Dan; Ll Guang
School of Electrical Engineering, Lhengzhou University , Lhengzhou 450001 , China
Keywords:
hierarchical fuzzy system;  particle swarm optimization algorithm; recursive least square algorithm
CLC:
TP273
DOI:
10.3969/ j. issn.1671 -6833.2015.04.003
Abstract:
In view of a new type of hierarchical fuzny system,a hybrid optimization algorithm is proposed inthis paper. The antecedent parameters of each fuzzy unit model are estimated by the particle swarm optimiza-tion algorithm,and the recursive least square algorithm is used to determine the parameters of consequents.Experiments on the well-known Box-Jenkins set data and the chaotic Mackey-Glass time series are carried out.The proposed hybrid optimization algorithm is compared with the fruit fly optimization algorithm and the inva-sive weed optimization algorithm. The result of experiments shows that the hybrid optimization algorithm canimprove the accuracy of the hierarchical fuzzy system model.
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