Rule-Set Optimization in Genetically-Generated Fuzzy Knowledge Bases

Marek Balazinski, Luc Baron, Sofiane Achiche

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

Abstract

Rule-set is considered as a key element in automatic generation of fuzzy knowledge bases (KB). This paper discusses the influence of the fuzzy-rule tuning on the quality of automatically KBs using a binary coded genetic algorithm (GA). The generated KBs have to satisfy a contradictory paradigm, in term of minimizing the approximation error and the complexity level of the KB. However, the focus is placed on the rule-set tuning of the KBs using specialized reproduction parameters of the GA. The technique is applied on theoretical and practical examples.
Original languageEnglish
Publication date2002
Publication statusPublished - 2002
Externally publishedYes
EventOptimization Days 2002 - Montréal, Québec, Canada
Duration: 1 Jan 2002 → …

Conference

ConferenceOptimization Days 2002
CityMontréal, Québec, Canada
Period01/01/2002 → …

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