relation: https://khub.utp.edu.my/scholars/1108/
title: A comparison of feed-forward back-propagation and radial basis artificial neural networks: A Monte Carlo study
creator: Abdalla, O.A.
creator: Zakaria, M.N.
creator: Sulaiman, S.
creator: Ahmad, W.F.W.
description: Interest in soft computing techniques, such as artificial neural networks (ANN) is growing rapidly. Feed-forward back-propagation and radial basis ANN are the most often used applications in this regard. They have been utilized to solve a number of real problems, although they gained a wide use, however the challenge remains to select the best of them in term of accuracy and efficiency performance. This paper presents a comparison between feed-forward back-propagation and radial basis ANN base on their performance. The comparison is performed using a Monte Carlo study that involves the following problems: addition, multiplication, division, powers and a production function. The result indicates that the proposed radial basis ANN results are significantly better than proposed feed-forward back-propagation ANN results for all five problems. © 2010 IEEE.
date: 2010
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Abdalla, O.A. and Zakaria, M.N. and Sulaiman, S. and Ahmad, W.F.W.  (2010) A comparison of feed-forward back-propagation and radial basis artificial neural networks: A Monte Carlo study.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049371848&doi=10.1109%2fITSIM.2010.5561599&partnerID=40&md5=28c8ebe2539493c5f724a81970f1526f
relation: 10.1109/ITSIM.2010.5561599
identifier: 10.1109/ITSIM.2010.5561599