AN IMPROVED GENETIC-ALGORITHM-BASED NEURAL-TUNED NEURAL NETWORK

被引:0
|
作者
Leung, F. H. F. [1 ]
Ling, S. H. [2 ]
Lam, H. K. [3 ]
机构
[1] Hong Kong Polytech Univ, Ctr Signal Proc, Dept Elect & Informat Engn, Kowloon, Hong Kong, Peoples R China
[2] Univ Western Australia, Sch Elect Elect & Comp Engn, Nedlands, WA 6009, Australia
[3] Kings Coll London Strand, Div Engn, London WC2R 2LS, England
关键词
Genetic algorithm; neural network; pattern recognition; sunspot forecasting;
D O I
10.1142/S1469026808002375
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a neural-tuned neural network (NTNN), which is trained by an improved genetic algorithm (GA). The NTNN consists of a common neural network and a modified neural network (MNN). In the MNN, a neuron model with two activation functions is introduced. An improved GA is proposed to train the parameters of the proposed network. A set of improved genetic operations are presented, which show superior performance over the traditional GA. The proposed network structure can increase the search space of the network and offer better performance than the traditional feed-forward neural network. Two application examples are given to illustrate the merits of the proposed network and the improved GA.
引用
收藏
页码:469 / 492
页数:24
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