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

Real-coded genetic algorithm with average-bound crossover and wavelet mutation for network parameters learning

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)
Ling, S.H. ; Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China ; Leung, F.H.F.

This paper presents the learning of neural network parameters using a real-coded genetic algorithm (RCGA) with proposed crossover and mutation. They are called the average-bound crossover (AveBXover) and wavelet mutation (WM). By introducing the proposed genetic operations, both the solution quality and stability are better than the RCGA with conventional genetic operations. A suite of benchmark test functions are used to evaluate the performance of the proposed algorithm. An application example on an associative memory neural network is used to show the learning performance brought by the proposed RCGA.

Published in:

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on  (Volume:2 )

Date of Conference:

31 July-4 Aug. 2005

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.