Algorithm Researching of RBF Neural Network Based on Improved PSO

Abstract:

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In view of the defect of particle swarm optimization which easily gets into partial extremum, the paper put out an improved particle swarm optimization, and applies the algorithm to the selecting of parameter of RBF neural network basal function. It searches the best parameter vector in the whole space, according to coding means, iterative formula, adapted function which the paper puts forwards. The experiment proves that RBF neural network based on improved PSO has faster convergent speed, and higher error precision.

Info:

Periodical:

Advanced Materials Research (Volumes 179-180)

Edited by:

Garry Zhu

Pages:

233-238

DOI:

10.4028/www.scientific.net/AMR.179-180.233

Citation:

H. Chen et al., "Algorithm Researching of RBF Neural Network Based on Improved PSO", Advanced Materials Research, Vols. 179-180, pp. 233-238, 2011

Online since:

January 2011

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Price:

$35.00

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