Radial Basis Function Neural Networks Optimization Algorithm Based on SVM

被引：0
|
作者：
Nong, Jifu [1 ]
机构：
[1] Guangxi Univ Nationalities, Coll Sci, Nanning, Peoples R China
来源：
COMMUNICATIONS AND INFORMATION PROCESSING, PT 2 | 2012年 / 289卷
关键词：
support vector machines; neural networks; genetic algorithm; system identification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Support vector machine (SVM) resembles RBF neural networks in structure. Considering their resemblance, a new optimization algorithm based on support vector machine and genetic algorithm for RBF neural network is presented, in which GA is used to choose the SVM model parameter and SVM is used to help constructing the RBF. The network based on this algorithm is applied on nonlinear system identification. Simulation results show that the network based on this algorithm has higher precision and better generalization ability.
引用
收藏
页码：291 / 298
页数：8
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