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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73823
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dc.contributor.authorRamos, Caio Cesar Oba-
dc.contributor.authorDe Souza, Andre Nunes-
dc.contributor.authorGastaldello, Danilo Sinkiti-
dc.contributor.authorPapa, João Paulo-
dc.date.accessioned2014-05-27T11:27:17Z-
dc.date.accessioned2016-10-25T18:40:02Z-
dc.date.available2014-05-27T11:27:17Z-
dc.date.available2016-10-25T18:40:02Z-
dc.date.issued2012-12-01-
dc.identifierhttp://dx.doi.org/10.1109/INDUSCON.2012.6451485-
dc.identifier.citation2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012.-
dc.identifier.urihttp://hdl.handle.net/11449/73823-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73823-
dc.description.abstractThis work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids. © 2012 IEEE.en
dc.language.isoeng-
dc.sourceScopus-
dc.subjectClassification technique-
dc.subjectCompetitive environment-
dc.subjectComputational tools-
dc.subjectIndustrial consumers-
dc.subjectIntelligent Algorithms-
dc.subjectNon-technical loss-
dc.subjectPower company-
dc.subjectRelevant features-
dc.subjectSmart grid-
dc.subjectElectric utilities-
dc.subjectIndustrial applications-
dc.subjectPrivatization-
dc.subjectApplication programs-
dc.titleIdentification and feature selection of non-technical losses for industrial consumers using the software WEKAen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartment of Electrical Engineering Polytechnic School University of São Paulo - USP, São Paulo-
dc.description.affiliationDepartment of Computing Faculty of Science São Paulo State University - UNESP, Bauru-
dc.description.affiliationUnespDepartment of Computing Faculty of Science São Paulo State University - UNESP, Bauru-
dc.identifier.doi10.1109/INDUSCON.2012.6451485-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartof2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012-
dc.identifier.scopus2-s2.0-84874399610-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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