By Topic

A simultaneous method for fuzzy memberships and rule optimization

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

3 Author(s)
Tang, K.S. ; Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong ; Chan, C.Y. ; Man, K.F.

A new scheme to optimize an optimal fuzzy subsets and rules is proposed. The method is derived by using genetic algorithms where the genes of the chromosome are classified into two types of genes. These genes can be arranged in a hierarchical form and one type of the genes control the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to be optimally reduced and yet, the system performance is well maintained. To justify this approach of fuzzy logic design, the proposed scheme is experimentally demonstrated by applying it to control a constant water pressure pumping system

Published in:

Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on

Date of Conference:

2-6 Dec 1996