Table of Contents
Conference Papers in Science
Volume 2014, Article ID 906376, 8 pages
http://dx.doi.org/10.1155/2014/906376
Conference Paper

Using Feed Forward Neural Network to Solve Eigenvalue Problems

Department of Mathematics, College of Education for Pure Science/Ibn Al-Haitham, Baghdad University, Baghdad, Iraq

Received 22 December 2013; Accepted 23 February 2014; Published 31 March 2014

Academic Editors: A. H. Bokhari and A. Jeribi

This Conference Paper is based on a presentation given by Luma N. M. Tawfiq at “The 3rd International Conference on Mathematical Sciences (ICMS3)” held from 17 December 2013 to 19 December 2013 in Kuala Lumpur, Malaysia.

Copyright © 2014 Luma N. M. Tawfiq and Othman M. Salih. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The aim of this paper is to presents a parallel processor technique for solving eigenvalue problem for ordinary differential equations using artificial neural networks. The proposed network is trained by back propagation with different training algorithms quasi-Newton, Levenberg-Marquardt, and Bayesian Regulation. The next objective of this paper was to compare the performance of aforementioned algorithms with regard to predicting ability.