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dc.contributor.advisor1Ribeiro, Moisés Vidal-
dc.contributor.advisor1Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4794613D7pt_BR
dc.contributor.referee1Aguiar, Eduardo Pestana de-
dc.contributor.referee1Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4236602D7pt_BR
dc.contributor.referee2Silva Junior, Ivo Chaves da-
dc.contributor.referee2Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4771513T6pt_BR
dc.contributor.referee3Guimarães, Frederico Gadelha-
dc.contributor.referee3Latteshttp://lattes.com.brpt_BR
dc.creatorAmaral, Renan Piazzaroli Finotti-
dc.creator.Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4860436U4pt_BR
dc.date.accessioned2018-01-22T16:10:30Z-
dc.date.available2018-01-09-
dc.date.available2018-01-22T16:10:30Z-
dc.date.issued2017-09-01-
dc.identifier.urihttps://repositorio.ufjf.br/jspui/handle/ufjf/6034-
dc.description.abstractThis thesis presents and discusses improvements in the type-1 and singleton fuzzy logic system for dealing with classification problems. Two training methods are addressed, the scaled conjugate gradient, which uses the second order information approximating the multiplication of the Hessian matrix H by the directional vector v (i.e. Hv), and the same method using the differential operator R {.} to compute the exact value of Hv. Also, in order to adapt the fuzzy model to handle multiclass classification problems, it is developed a novel fuzzy model with a vector as output. All proposals are tested through the performance metrics analysis based on data sets provided by UCI Machine Learning Repository. The reported results show the high convergence speed and better classification rates of the proposed training methods than others presented in the literature. Additionally, the novel fuzzy model has a significant reduction in computational and classifier complexity, especially when the number of classes in classification problem increases.pt_BR
dc.description.resumo-pt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Juiz de Fora (UFJF)pt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICE – Instituto de Ciências Exataspt_BR
dc.publisher.programPrograma de Pós-graduação em Engenharia Elétricapt_BR
dc.publisher.initialsUFJFpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectFuzzy logic systempt_BR
dc.subjectMulticlass classificationpt_BR
dc.subjectScaled conjugate gradientpt_BR
dc.subjectHessianfreept_BR
dc.subject.cnpqCNPQ::ENGENHARIAS::ENGENHARIA ELETRICApt_BR
dc.titleType-1 and singleton fuzzy logic system trained by a fast scaled conjugate gradient methods for dealing with classification problemspt_BR
dc.typeDissertaçãopt_BR
Appears in Collections:Mestrado em Engenharia Elétrica (Dissertações)



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