Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1808129325763919872 |