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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73077
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dc.contributor.authorRamos, Caio C. O.-
dc.contributor.authorSouza, André N.-
dc.contributor.authorNakamura, Rodrigo Y. M.-
dc.contributor.authorPapa, João Paulo-
dc.date.accessioned2014-05-27T11:26:20Z-
dc.date.accessioned2016-10-25T18:36:20Z-
dc.date.available2014-05-27T11:26:20Z-
dc.date.available2016-10-25T18:36:20Z-
dc.date.issued2011-12-21-
dc.identifierhttp://dx.doi.org/10.1109/ISAP.2011.6082217-
dc.identifier.citation2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011.-
dc.identifier.urihttp://hdl.handle.net/11449/73077-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73077-
dc.description.abstractNon-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.en
dc.language.isoeng-
dc.sourceScopus-
dc.subjectClustering-
dc.subjectNon-technical Losses-
dc.subjectOptimum-Path Forest-
dc.subjectPattern Recognition-
dc.subjectClustering techniques-
dc.subjectData clustering-
dc.subjectData sets-
dc.subjectElectric power company-
dc.subjectNon-technical loss-
dc.subjectSpecific profile-
dc.subjectClustering algorithms-
dc.subjectCrime-
dc.subjectData processing-
dc.subjectElectric utilities-
dc.subjectIndustry-
dc.subjectIntelligent systems-
dc.subjectPattern recognition-
dc.subjectPower transmission-
dc.subjectForestry-
dc.subjectAlgorithms-
dc.subjectArtificial Intelligence-
dc.subjectData Processing-
dc.subjectElectric Power Transmission-
dc.subjectElectricity-
dc.subjectLosses-
dc.titleElectrical consumers data clustering through optimum-path foresten
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartment of Electrical Engineering University of São Paulo, São Paulo, São Paulo-
dc.description.affiliationDepartment of Computing UNESP - Univ. Estadual Paulista, Bauru, São Paulo-
dc.description.affiliationUnespDepartment of Computing UNESP - Univ. Estadual Paulista, Bauru, São Paulo-
dc.identifier.doi10.1109/ISAP.2011.6082217-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartof2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011-
dc.identifier.scopus2-s2.0-83655211673-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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