Design of RBF Neural Networks Based on Adjustable Radius

Abstract:

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In this paper, a new RBF neural network (RBFNN) algorithm, called ar-RBFNN, is presented. In traditional RBFNNs based on clustering algorithm, called oRBFNN in this paper, the width of the basis function-Gaussian function, or called radius, ignored the effect of numbers in different clusters, or density of data points. New algorithm considers radius is effect to performance of algorithms in problem of function approximation. Mean Square Error is used to evaluate performances of two algorithms, oRBFNN and ar-RBFNN algorithms. Several experiments in function approximation show ar-RBFNN is better than oRBFNN.

Info:

Periodical:

Key Engineering Materials (Volumes 439-440)

Edited by:

Yanwen Wu

Pages:

605-610

DOI:

10.4028/www.scientific.net/KEM.439-440.605

Citation:

X. Y. Liu "Design of RBF Neural Networks Based on Adjustable Radius", Key Engineering Materials, Vols. 439-440, pp. 605-610, 2010

Online since:

June 2010

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Price:

$35.00

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