By Topic

A fast and reliable routing algorithm based on Hopfield Neural Networks optimized by Particle Swarm Optimization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Bastos-Filho, C.J.A. ; Dept. of Comput. Syst., Univ. of Pernambuco, Recife ; Schuler, W.H. ; Oliveira, A.L.I.

Routing is very important for computer networks because it is one of the main factors that influences network performance. In this paper, we propose an improved intelligent method for routing based on Hopfield Neural Networks (HANN), which uses a discrete equation and the Particle Swarm Optimization (PSO) technique to optimize the HNN parameters. The fitness function for the PSO algorithm used here is a combination of the number of iterations for convergence and the percentage error when the HNN method tries to find the best path in a communication network. The simulation results show that PSO is a reliable approach to optimize the Hopfield network for routing in computer networks, since this method results in fast convergence and produces accurate results.

Published in:

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Date of Conference:

1-8 June 2008