DocumentCode :
2729566
Title :
A genetic algorithm based neural-tuned neural network
Author :
Ling, S.H. ; Lam, H.K. ; Leung, Frank H. F. ; Lee, YS
Author_Institution :
Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China
Volume :
3
fYear :
2003
fDate :
2-6 Nov. 2003
Firstpage :
2423
Abstract :
This paper presents a neural-tuned neural network, which is trained by genetic algorithm (GA). The neural-tuned neural network consists of a neural network and a modified neural network. In the modified neural network, a neuron model with two activation functions is introduced. Some parameters of these activation functions is tuned by neural network. The proposed network structure can increase the search space of the network and gives better performance than traditional feedforward neural networks. Some application examples are given to illustrate the merits of the proposed network.
Keywords :
genetic algorithms; multilayer perceptrons; dynamic activation function; feedforward neural networks; genetic algorithm; neural-tuned neural network; pattern recognition; static activation function; sunspot forecasting; Control system synthesis; Feedforward neural networks; Feedforward systems; Genetic algorithms; Modeling; Multi-layer neural network; Neural networks; Neurons; Pattern recognition; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, 2003. IECON '03. The 29th Annual Conference of the IEEE
Print_ISBN :
0-7803-7906-3
Type :
conf
DOI :
10.1109/IECON.2003.1280624
Filename :
1280624
Link To Document :
بازگشت