By Topic

Research on input variable selection for numeric data based fuzzy modeling

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
$33 $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

4 Author(s)
Zong-Yi Xing ; China Acad. of Railway Sci., Beijing, China ; Li-Min Jia ; Yong Qin ; Tao Lei

The first step to system modeling and control is input variable selection. Based on fast fuzzy modeling algorithm and input variable selection criterion, a simple and effective method for selecting input variables when building a Takagi-Sugeno fuzzy model is proposed. This method is applied to two well-known benchmark examples. Simulation results clearly show the effectiveness of the algorithm.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:5 )

Date of Conference:

2-5 Nov. 2003