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dc.contributor.authorSouza, Andre N. [UNESP]
dc.contributor.authorda Costa, Pedro [UNESP]
dc.contributor.authorda Silva, Paulo S. [UNESP]
dc.contributor.authorRamos, Caio C. O.
dc.contributor.authorPapa, Joao P. [UNESP]
dc.date.accessioned2014-05-20T13:25:56Z
dc.date.available2014-05-20T13:25:56Z
dc.date.issued2012-01-01
dc.identifierhttp://dx.doi.org/10.1080/08839514.2012.674289
dc.identifier.citationApplied Artificial Intelligence. Philadelphia: Taylor & Francis Inc, v. 26, n. 5, p. 503-515, 2012.
dc.identifier.issn0883-9514
dc.identifier.urihttp://hdl.handle.net/11449/8274
dc.description.abstractIn this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.en
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent503-515
dc.language.isoeng
dc.publisherTaylor & Francis Inc
dc.relation.ispartofApplied Artificial Intelligence
dc.sourceWeb of Science
dc.titleEFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FORESTen
dc.typeArtigo
dcterms.licensehttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dcterms.rightsHolderTaylor & Francis Inc
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.description.affiliationUniv São Paulo, Dept Elect Engn, São Paulo, Brazil
dc.description.affiliationSão Paulo State Univ, Dept Elect Engn, Bauru, Brazil
dc.description.affiliationSão Paulo State Univ, Dept Comp, Bauru, Brazil
dc.description.affiliationUnespSão Paulo State Univ, Dept Elect Engn, Bauru, Brazil
dc.description.affiliationUnespSão Paulo State Univ, Dept Comp, Bauru, Brazil
dc.identifier.doi10.1080/08839514.2012.674289
dc.identifier.wosWOS:000303887700004
dc.rights.accessRightsAcesso restrito
dc.description.sponsorshipIdFAPESP: 10/12398-0
dc.description.sponsorshipIdFAPESP: 09/16206-1
dc.description.sponsorshipIdCNPq: 303182/2011-3
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Baurupt
dc.identifier.lattes8212775960494686
unesp.author.lattes8212775960494686[1]
unesp.author.orcid0000-0003-1495-633X[2]
unesp.author.orcid0000-0002-6494-7514[5]
unesp.author.orcid0000-0002-8617-5404[1]
dc.relation.ispartofjcr0.587
dc.relation.ispartofsjr0,273
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