A method of improving performance of fuzzy neural network based on Differential Evolution

被引:1
|
作者
Ma, Ming [1 ]
Xu, Yan [1 ]
Zhang, Li-Biao [2 ]
机构
[1] Beihua Univ, Informat Manage Ctr, Jilin 132013, Peoples R China
[2] Jilin Univ, Coll Comp Sci &Technol, Changchun 130012, Peoples R China
关键词
differential evoltion; fuzzy neural network; fuzzy rule;
D O I
10.1109/ICMLC.2008.4620527
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Differential evolution is a powerful evolutionary inspired search technique for global optimization. We have proposed a new algorithm based on differential Evolution to solve the fuzzy neural network design problem, it can identify an optimal and efficient fuzzy, neural network structure for a given problem. Numerical simulations show the effectiveness of the proposed algorithm.
引用
收藏
页码:874 / +
页数:2
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