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Fuzzy model identification by evolutionary, gradient based and memtic algorithms

2008Conference object Restricted access
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dc.contributor.authorBotzheim, J.
dc.contributor.authorKóczy, László T.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-12T11:58:00Z
dc.date.available2013-02-12T11:58:00Z
dc.date.issued2008
dc.date.updated2013-01-30T16:19:25Z
dc.description.abstractOne of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.pt_PT
dc.identifier.citationBotzheim, J.; Koczy, Laszlo T.; Ruano, A. E. Fuzzy Model Identification by Evolutionary, Gradient Based and Memtic Algorithms, Trabalho apresentado em Gyor Symposium on Computational Intelligence, In Proceedings of the Gyor Symposium on Computational Intelligence, Gyor, 2008.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2316
dc.language.isoengpor
dc.peerreviewedyespor
dc.titleFuzzy model identification by evolutionary, gradient based and memtic algorithmspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceGyorpor
oaire.citation.endPage56por
oaire.citation.startPage52por
oaire.citation.titleGyor Symposium on Computational Intelligencepor
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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