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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72586
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dc.contributor.authorRamos, Caio C. O.-
dc.contributor.authorPapa, João Paulo-
dc.contributor.authorSouza, André N.-
dc.contributor.authorChiachia, Giovani-
dc.contributor.authorFalcão, Alexandre X.-
dc.date.accessioned2014-05-27T11:25:57Z-
dc.date.accessioned2016-10-25T18:34:16Z-
dc.date.available2014-05-27T11:25:57Z-
dc.date.available2016-10-25T18:34:16Z-
dc.date.issued2011-08-02-
dc.identifierhttp://dx.doi.org/10.1109/ISCAS.2011.5937748-
dc.identifier.citationProceedings - IEEE International Symposium on Circuits and Systems, p. 1045-1048.-
dc.identifier.issn0271-4310-
dc.identifier.urihttp://hdl.handle.net/11449/72586-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72586-
dc.description.abstractAlthough non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention in this context. In this paper, we focus on this problem applying a novel feature selection algorithm based on Particle Swarm Optimization and Optimum-Path Forest. The results demonstrated that this method can improve the classification accuracy of possible frauds up to 49% in some datasets composed by industrial and commercial profiles. © 2011 IEEE.en
dc.format.extent1045-1048-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectAutomatic identification-
dc.subjectClassification accuracy-
dc.subjectData sets-
dc.subjectFeature selection algorithm-
dc.subjectIdentification accuracy-
dc.subjectNon-technical loss-
dc.subjectAutomation-
dc.subjectClassification (of information)-
dc.subjectParticle swarm optimization (PSO)-
dc.subjectFeature extraction-
dc.titleWhat is the importance of selecting features for non-technical losses identification?en
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)-
dc.description.affiliationDepartment of Electrical Engineering USP - University of São Paulo, São Paulo-
dc.description.affiliationDepartment of Computing UNESP - São Paulo State University, Bauru, São Paulo-
dc.description.affiliationDepartment of Electrical Engineering UNESP - São Paulo State University, Bauru, São Paulo-
dc.description.affiliationInstitute of Computing University of Campinas, São Paulo-
dc.description.affiliationUnespDepartment of Computing UNESP - São Paulo State University, Bauru, São Paulo-
dc.description.affiliationUnespDepartment of Electrical Engineering UNESP - São Paulo State University, Bauru, São Paulo-
dc.identifier.doi10.1109/ISCAS.2011.5937748-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofProceedings - IEEE International Symposium on Circuits and Systems-
dc.identifier.scopus2-s2.0-79960865826-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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