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
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;
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
DOI :
10.1109/ICMLC.2008.4620527
