Optimization of fuzzy rule sets using a bacterial evolutionary algorithm

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Document typeArticle
Defense date2008
PublisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Rights accessOpen Access
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Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
In this paper we present a novel approach where we rst create a large
set of (possibly) redundant rules using inductive rule learning and where we
use a bacterial evolutionary algorithm to identify the best subset of rules in a
subsequent step. This enables us to nd an optimal rule set with respect to a
freely de nable global goal function, which gives us the possibility to integrate
interpretability related quality criteria explicitly in the goal function and to
consider the interplay of the overlapping fuzzy rules
CitationDrobics, Mario; Botzheim, J. Optimization of fuzzy rule sets using a bacterial evolutionary algorithm. "Mathware & Soft Computing", vol. 15, núm. 1, p. 21-40.
ISSN1134-5632
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