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Solving a system of nonlinear integral equations by an RBF network

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journal contribution
posted on 2009-05-01, 00:00 authored by A Golbabai, Musa MammadovMusa Mammadov, S Seifollahi
In this paper, a novel learning strategy for radial basis function networks (RBFN) is proposed. By adjusting the parameters of the hidden layer, including the RBF centers and widths, the weights of the output layer are adapted by local optimization methods. A new local optimization algorithm based on a combination of the gradient and Newton methods is introduced. The efficiency of some local optimization methods to update the weights of RBFN is studied in solving systems of nonlinear integral equations. © 2009 Elsevier Ltd. All rights reserved.

History

Journal

Computers and Mathematics with Applications

Volume

57

Pagination

1651-1658

Location

Amsterdam, The Netherlands

Open access

  • Yes

ISSN

0898-1221

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

10

Publisher

Elsevier

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