dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:27:17Z
dc.date.accessioned2022-10-05T18:38:04Z
dc.date.available2014-05-27T11:27:17Z
dc.date.available2022-10-05T18:38:04Z
dc.date.created2014-05-27T11:27:17Z
dc.date.issued2012-12-01
dc.identifier2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012.
dc.identifierhttp://hdl.handle.net/11449/73823
dc.identifier10.1109/INDUSCON.2012.6451485
dc.identifier2-s2.0-84874399610
dc.identifier9039182932747194
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3922801
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.
dc.languageeng
dc.relation2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012
dc.rightsAcesso aberto
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 WEKA
dc.typeTrabalho apresentado em evento


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