DocumentCode :
1807727
Title :
WNN optimization design based on Artificial Fish-Swarm Algorithm
Author :
Xueqin, Tang ; Jingshun, Duanmu ; Liya, Jin ; Zongchang, Xu
Author_Institution :
Dept. of Technol. Support Eng., Acad. of Armored Force Eng., Beijing, China
Volume :
4
fYear :
2011
fDate :
24-26 Dec. 2011
Firstpage :
2747
Lastpage :
2750
Abstract :
The problem such as parameters initialization and network structure determination is collectively referred to as the WNN optimization design. Aiming at the effect on the performance of WNN, an optimization design algorithm, which is based on Artificial Fish-Swarm Algorithm(AFSA), is proposed. The AFSA can synchronously determine the initial values of parameters and hidden layer nodes number in search space. The simulation results show it is an effective algorithm, which not only has higher accuracy and faster convergence rate but also can avoid the blindness of the WNN optimization design.
Keywords :
feedforward neural nets; optimisation; WNN optimization design; artificial fish swarm algorithm; network structure; parameters initialization; Mathematical model; artificial fish-swarm algorithm(AFSA); optimization design; wavelet neural network(WNN);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
Type :
conf
DOI :
10.1109/ICCSNT.2011.6182534
Filename :
6182534
Link To Document :
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