DocumentCode
476007
Title
A method of improving performance of fuzzy neural network based on differential evolution
Author
Ma, Ming ; Xu, Yan ; Zhang, Li-Biao
Author_Institution
Inf. Manage Center, Beihua Univ., Jilin
Volume
2
fYear
2008
fDate
12-15 July 2008
Firstpage
874
Lastpage
877
Abstract
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.
Keywords
evolutionary computation; fuzzy neural nets; optimisation; differential evolution; fuzzy neural network design problem; fuzzy neural network structure; global optimization; search technique; Chromium; Computer network management; Conference management; Cybernetics; Energy management; Fuzzy control; Fuzzy neural networks; Genetic mutations; Machine learning; Neural networks; Differential evolution; Fuzzy neural network; Fuzzy rule;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620527
Filename
4620527
Link To Document