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Bacterial memetic algorithm for fuzzy rule base optimization

dc.contributor.authorCabrita, Cristiano Lourenço
dc.contributor.authorBotzheim, J.
dc.contributor.authorGedeon, Tamas D.
dc.contributor.authorRuano, Antonio
dc.contributor.authorKóczy, László T.
dc.contributor.authorFonseca, C. M.
dc.date.accessioned2013-02-07T13:58:53Z
dc.date.available2013-02-07T13:58:53Z
dc.date.issued2007
dc.date.updated2013-01-26T18:44:37Z
dc.description.abstractIn our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The Levenberg-Marquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques – the bacterial memetic algorithm – was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base.por
dc.identifier.citationCabrita, Cristiano; Botzheim, Janos; Gedeon, Tamas D.; Ruano, Antonio E.; Koczy, Laszlo T.; Fonseca, Carlos. Bacterial Memetic Algorithm for Fuzzy Rule Base Optimization, Trabalho apresentado em 2006 World Automation Congress, In Proceedings of the 2006 World Automation Congress, Budapest, Hungary, 2006.por
dc.identifier.isbn1889335339
dc.identifier.otherAUT: ARU00698; CCA01443;
dc.identifier.urihttp://hdl.handle.net/10400.1/2250
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherIEEEpor
dc.subjectFuzzy rule basepor
dc.subjectBacterial algorithmpor
dc.subjectLevenberg-Marquardt methodpor
dc.subjectMemetic algorithmpor
dc.titleBacterial memetic algorithm for fuzzy rule base optimizationpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBudapest, Hungarypor
oaire.citation.endPage26por
oaire.citation.startPage24por
oaire.citation.titleWorld Automation Congresspor
person.familyNameCabrita
person.familyNameRuano
person.givenNameCristiano Lourenço
person.givenNameAntonio
person.identifier.ciencia-idFF1E-13A0-A269
person.identifier.orcid0000-0003-4946-0465
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id55958626100
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication081b091f-c9fa-470a-9a28-51fe4c85864a
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery081b091f-c9fa-470a-9a28-51fe4c85864a

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