A study on the discovery of relevant fuzzy rules usingpseudobacterial genetic algorithm
Nawa, N.E.
Furuhashi, T.
Hashiyama, T.
Uchikawa, Y.
Dept. of Inf. Electron., Nagoya Univ.;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Dec 1999
Volume: 46,
Issue: 6
On page(s): 1080-1089
ISSN: 0278-0046
References Cited: 15
CODEN: ITIED6
INSPEC Accession Number: 6443307
Digital Object Identifier: 10.1109/41.807990
Current Version Published: 2002-08-06
Abstract
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
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