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Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

2003Journal article Open access
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dc.contributor.authorCabrita, Cristiano Lourenço
dc.contributor.authorBotzheim, J.pt_PT
dc.contributor.authorRuano, Antonio
dc.contributor.authorKóczy, László T.pt_PT
dc.date.accessioned2009-02-13T17:09:15Z
dc.date.available2009-02-13T17:09:15Z
dc.date.issued2003
dc.description.abstractIn the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.pt_PT
dc.formatapplication/pdfpt_PT
dc.identifier.citationIFAC International Conference on Intelligent control Systems and Signal Processing (ICONS). - Faro, 8-11 Abril 2003. - 6 ppt_PT
dc.identifier.otherAUT: ARU00698; CCA01443;
dc.identifier.urihttp://hdl.handle.net/10400.1/50
dc.language.isoengpt_PT
dc.publisherFaropt_PT
dc.relation.urihttp://www.bib.ualg.pt/artigos/DocentesEST/CABGen.pdfpt_PT
dc.rights.uriopenAccessen
dc.subjectControlo automáticopt_PT
dc.subjectRedes neuronaispt_PT
dc.subjectSistemas fuzzypt_PT
dc.subjectProgramação genéticapt_PT
dc.subjectAlgoritmo bacterianopt_PT
dc.subject681.5pt_PT
dc.subjectConstructive algorithmspt_PT
dc.subjectB-splinespt_PT
dc.subjectGenetic programmingpt_PT
dc.subjectBacterial evolutionary algorithmpt_PT
dc.subjectFuzzy rule basept_PT
dc.titleGenetic programming and bacterial algorithm for neural networks and fuzzy systems designpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage448
oaire.citation.startPage443
oaire.citation.titleIFAC International Conference on Intelligent control Systems and Signal Processing (ICONS), Faro, 8-11 Abril 2003
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.typearticlept_PT
relation.isAuthorOfPublication081b091f-c9fa-470a-9a28-51fe4c85864a
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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