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

Performance comparison of neural network models for engineering problems

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)
Sung, A.H. ; Dept. of Comput. Sci., New Mexico Inst. of Min. & Technol., Socorro, NM, USA ; Jun Lin

This paper addresses the issue of identifying important input parameters in building a multilayer, backpropagation network (BPN). Since the identification of important and/or redundant input parameters of a BPN leads to reduced size, shortened training time, and possibly more accurate results of the network, it is an issue of great practical as well as theoretical interests. We compare three different methods that have been proposed for identifying important inputs-sensitivity analysis, fuzzy curves, and change of MSE-and analyze their effectiveness on BPNs trained to model simple nonlinear functions as well as a real, production use network that has been built to model the cement bonding quality in a petroleum engineering application. Based on the analysis and our experience in building the BPN for predicting cement bonding quality, we also propose a general methodology for building BPNs in engineering applications

Published in:

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on  (Volume:4 )

Date of Conference:

12-15 Oct 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.