ldentification of Hierarchical Fuzzy System Based on HybridOptimization Algorithm
[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
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
- 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.
- References:
- -
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