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

A nonlinear combining forecast method based on fuzzy neural network

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

1 Author(s)
Jing-Rong Dong ; Dept. of Mathematic & Comput. Sci., Chongqing Normal Univ., China

It has been shown in previous economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively focused on linear combined forecasts. The issues and methods of nonlinear combined forecasts have not yet been fully explored, even though forecast improvements may be possible using nonlinear combination techniques. We investigate the fuzzy neural network (FNN) as a tool for nonlinear combined forecasts. The performance of the networks is evaluated by comparing them to two individual forecasting methods and three conventional linear combining methods. The outcome of the comparison proved that the prediction by the FNN method generally performs better than those by individual forecasting methods, as well as linear combining methods. The paper suggests that the FNN method can be used as an alternative to conventional linear combining methods to achieve greater forecasting accuracy. Superiority of the FNN arises because of its flexibility in accounting for potentially complex nonlinear relationships not easily captured by traditional linear models.

Published in:

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on  (Volume:4 )

Date of Conference:

4-5 Nov. 2002

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.