By Topic

A study on the discovery of relevant fuzzy rules using pseudobacterial genetic algorithm

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

4 Author(s)
Nawa, N.E. ; Dept. of Inf. Electron., Nagoya Univ., Japan ; Furuhashi, T. ; Hashiyama, T. ; Uchikawa, Y.

This paper presents a new method for the discovery of relevant fuzzy rules using the pseudobacterial genetic algorithm (PBGA). The PBGA was proposed by the authors as a new approach combining a genetic algorithm with a local improvement mechanism inspired by a process in bacterial genetics, named bacterial operation. The presented system aims at the improvement of the quality of the generated fuzzy rules, producing blocks of effective rules and more compact rule bases. This is achieved by encoding the fuzzy rules in the chromosomes in a suitable form in order to make the bacterial operation more effective and by using a crossover operation that adaptively decides the cutting points according to the distribution of degrees of truth values of the rules. In this paper, first, results obtained when using the PBGA for a simple fuzzy modeling problem are presented and compared with other methods. Second, the PBGA is used in the design of a fuzzy logic controller for a semi-active suspension system. The results show the benefits obtained with this approach in both of the studied cases

Published in:

Industrial Electronics, IEEE Transactions on  (Volume:46 ,  Issue: 6 )