Identification and feature selection of non-technical losses for industrial consumers using the software WEKA

Detalhes bibliográficos
Autor(a) principal: Ramos, Caio Cesar Oba
Data de Publicação: 2012
Outros Autores: De Souza, Andre Nunes, Gastaldello, Danilo Sinkiti, Papa, João Paulo [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/INDUSCON.2012.6451485
http://hdl.handle.net/11449/73823
Resumo: This 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.
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spelling Identification and feature selection of non-technical losses for industrial consumers using the software WEKAClassification techniqueCompetitive environmentComputational toolsIndustrial consumersIntelligent AlgorithmsNon-technical lossPower companyRelevant featuresSmart gridElectric utilitiesIndustrial applicationsPrivatizationApplication programsThis 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.Department of Electrical Engineering Polytechnic School University of São Paulo - USP, São PauloDepartment of Computing Faculty of Science São Paulo State University - UNESP, BauruDepartment of Computing Faculty of Science São Paulo State University - UNESP, BauruUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Ramos, Caio Cesar ObaDe Souza, Andre NunesGastaldello, Danilo SinkitiPapa, João Paulo [UNESP]2014-05-27T11:27:17Z2014-05-27T11:27:17Z2012-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/INDUSCON.2012.64514852012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012.http://hdl.handle.net/11449/7382310.1109/INDUSCON.2012.64514852-s2.0-848743996109039182932747194Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012info:eu-repo/semantics/openAccess2024-04-23T16:11:33Zoai:repositorio.unesp.br:11449/73823Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:29:31.910867Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
title Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
spellingShingle Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
Ramos, Caio Cesar Oba
Classification technique
Competitive environment
Computational tools
Industrial consumers
Intelligent Algorithms
Non-technical loss
Power company
Relevant features
Smart grid
Electric utilities
Industrial applications
Privatization
Application programs
title_short Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
title_full Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
title_fullStr Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
title_full_unstemmed Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
title_sort Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
author Ramos, Caio Cesar Oba
author_facet Ramos, Caio Cesar Oba
De Souza, Andre Nunes
Gastaldello, Danilo Sinkiti
Papa, João Paulo [UNESP]
author_role author
author2 De Souza, Andre Nunes
Gastaldello, Danilo Sinkiti
Papa, João Paulo [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Ramos, Caio Cesar Oba
De Souza, Andre Nunes
Gastaldello, Danilo Sinkiti
Papa, João Paulo [UNESP]
dc.subject.por.fl_str_mv Classification technique
Competitive environment
Computational tools
Industrial consumers
Intelligent Algorithms
Non-technical loss
Power company
Relevant features
Smart grid
Electric utilities
Industrial applications
Privatization
Application programs
topic Classification technique
Competitive environment
Computational tools
Industrial consumers
Intelligent Algorithms
Non-technical loss
Power company
Relevant features
Smart grid
Electric utilities
Industrial applications
Privatization
Application programs
description This 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.
publishDate 2012
dc.date.none.fl_str_mv 2012-12-01
2014-05-27T11:27:17Z
2014-05-27T11:27:17Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/INDUSCON.2012.6451485
2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012.
http://hdl.handle.net/11449/73823
10.1109/INDUSCON.2012.6451485
2-s2.0-84874399610
9039182932747194
url http://dx.doi.org/10.1109/INDUSCON.2012.6451485
http://hdl.handle.net/11449/73823
identifier_str_mv 2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012.
10.1109/INDUSCON.2012.6451485
2-s2.0-84874399610
9039182932747194
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2012 10th IEEE/IAS International Conference on Industry Applications, INDUSCON 2012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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