Solving a system of nonlinear integral equations by an RBF network

Golbabai A., MƏMMƏDOV M., Seifollahi S.

Computers and Mathematics with Applications, vol.57, no.10, pp.1651-1658, 2009 (SCI-Expanded, Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Cild: 57 Say: 10
  • Nəşr tarixi: 2009
  • Doi nömrəsi: 10.1016/j.camwa.2009.03.038
  • jurnalın adı: Computers and Mathematics with Applications
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Səhifə sayı: pp.1651-1658
  • Açar sözlər: Continuous optimization, Gradient method, Newton's method, RBF network, System of nonlinear integral equations
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Bəli

Qısa məlumat

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.