A Method for Training RBF Neural Networks Based on Population Migration Algorithm

Author

Zhang, Weiwei ; Luo, Qifang ; Zhou, Yongquan

Author_Institution

Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China

Volume

1

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

165

Lastpage

169

Abstract

This paper proposes a new global optimization technique in which combines population migration algorithm (PMA) and radial basis function (RBF) neural networks learning algorithm for training RBF neural network. Compared with the traditional RBF training algorithm, the simulation results show that the method has a higher accuracy in a stringency and works well in avoiding sticking in local minima.

Keywords

learning (artificial intelligence); optimisation; radial basis function networks; RBF neural networks; neural network training; population migration algorithm; radial basis function network; Artificial intelligence; Artificial neural networks; Biological neural networks; Computational modeling; Feedforward neural networks; Function approximation; Information processing; Neural networks; Optimization methods; Radial basis function networks; RBF neural networks; global optimization; population migration algorithm; weight;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.35

Filename

5376069