Cart (Loading....) | Create Account
Close category search window
 

Neural net approximations to solutions of systems of fuzzy linear equations

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

2 Author(s)
Buckley, J.J. ; Dept. of Math., Alabama Univ., Birmingham, AL, USA ; Hayashi, Y.

This paper continues previous research (Buckley and Eslami, 1995, Buckley and Hayashi, 1995, Hayashi and Buckley,1996) into using neural nets to solve fuzzy problems. We show how to train neural nets, with certain sign constraints on their weights, using genetic algorithms, to approximate solutions to systems of fuzzy linear equations. This paper presents a new application of layered, feedforward, neural nets with sign restrictions on their weights

Published in:

Neural Networks,1997., International Conference on  (Volume:4 )

Date of Conference:

9-12 Jun 1997

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.