DocumentCode
2522039
Title
A fuzzy neural network algorithm based on GA
Author
Jingmin, Wei ; Jiafu, Tang ; Huanjie, Liu
Author_Institution
Polytech. Sch., Inf. Eng. Dept., Shenyang Ligong Univ., Fushun, China
fYear
2011
fDate
23-25 May 2011
Firstpage
3044
Lastpage
3048
Abstract
Firstly fuzzy neural network algorithm and its advantages are introduced, Combining modified genetic algorithm (MGA) and Minus-Grade Decline a fuzzy neural network (FBPNN) algorithm based on two phases is proposed in this paper. In the first phases fuzzy neural network in global area is optimized with genetic algorithm (GA) and in the second phases in local area is optimized with Minus-Grade Decline. Using this kind of combined optimization algorithm the self-learning and robust can be increased in the networks.
Keywords
fuzzy neural nets; genetic algorithms; unsupervised learning; combined optimization algorithm; fuzzy neural network algorithm; minus grade decline; modified genetic algorithm; self-learning; Artificial neural networks; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Modeling; Optimization; Training; FBPNN; GA; Minus-Grade Decline;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location
Mianyang
Print_ISBN
978-1-4244-8737-0
Type
conf
DOI
10.1109/CCDC.2011.5968776
Filename
5968776
Link To Document