Data-driven identification of operating patterns in a thermal power plant by clustering methods

Detalhes bibliográficos
Autor(a) principal: Duarte, Jéssica
Data de Publicação: 2020
Outros Autores: Vieira, Lara Werncke, Marques, Augusto Delavald, Schneider, Paulo Smith, Oliveira, Guilherme Lacerda Batista de
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/217873
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spelling Duarte, JéssicaVieira, Lara WernckeMarques, Augusto DelavaldSchneider, Paulo SmithOliveira, Guilherme Lacerda Batista deIbero-Latin-American Congress on Computational Methods in Engineering (41. : 2020.mario roland : On-line)2021-02-10T04:14:48Z20202675-6269http://hdl.handle.net/10183/217873001120575application/pdfengIberian Latin-American Congress on Computational Methods in Engineering (41. : 2020 : On-line). Proceedings [recurso eletrônico]. São Paulo: ABMEC, 2020.Usinas termelétricasAnálise de dadosPower plant operationOperation patternsOperation parametersK-means clusteringPrincipal component analysis (PCA)Data-driven identification of operating patterns in a thermal power plant by clustering methodsinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001120575.pdf.txt001120575.pdf.txtExtracted Texttext/plain25197http://www.lume.ufrgs.br/bitstream/10183/217873/2/001120575.pdf.txtb57768c37dce190860f8a9305ba2d2e2MD52ORIGINAL001120575.pdfTexto completo (inglês)application/pdf508685http://www.lume.ufrgs.br/bitstream/10183/217873/1/001120575.pdf74900aa64802788bbee59ae9baeb0ba5MD5110183/2178732021-03-09 04:50:45.284008oai:www.lume.ufrgs.br:10183/217873Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-03-09T07:50:45Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Data-driven identification of operating patterns in a thermal power plant by clustering methods
title Data-driven identification of operating patterns in a thermal power plant by clustering methods
spellingShingle Data-driven identification of operating patterns in a thermal power plant by clustering methods
Duarte, Jéssica
Usinas termelétricas
Análise de dados
Power plant operation
Operation patterns
Operation parameters
K-means clustering
Principal component analysis (PCA)
title_short Data-driven identification of operating patterns in a thermal power plant by clustering methods
title_full Data-driven identification of operating patterns in a thermal power plant by clustering methods
title_fullStr Data-driven identification of operating patterns in a thermal power plant by clustering methods
title_full_unstemmed Data-driven identification of operating patterns in a thermal power plant by clustering methods
title_sort Data-driven identification of operating patterns in a thermal power plant by clustering methods
author Duarte, Jéssica
author_facet Duarte, Jéssica
Vieira, Lara Werncke
Marques, Augusto Delavald
Schneider, Paulo Smith
Oliveira, Guilherme Lacerda Batista de
author_role author
author2 Vieira, Lara Werncke
Marques, Augusto Delavald
Schneider, Paulo Smith
Oliveira, Guilherme Lacerda Batista de
author2_role author
author
author
author
dc.contributor.event.pt_BR.fl_str_mv Ibero-Latin-American Congress on Computational Methods in Engineering (41. : 2020.mario roland : On-line)
dc.contributor.author.fl_str_mv Duarte, Jéssica
Vieira, Lara Werncke
Marques, Augusto Delavald
Schneider, Paulo Smith
Oliveira, Guilherme Lacerda Batista de
dc.subject.por.fl_str_mv Usinas termelétricas
Análise de dados
topic Usinas termelétricas
Análise de dados
Power plant operation
Operation patterns
Operation parameters
K-means clustering
Principal component analysis (PCA)
dc.subject.eng.fl_str_mv Power plant operation
Operation patterns
Operation parameters
K-means clustering
Principal component analysis (PCA)
publishDate 2020
dc.date.issued.fl_str_mv 2020
dc.date.accessioned.fl_str_mv 2021-02-10T04:14:48Z
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Iberian Latin-American Congress on Computational Methods in Engineering (41. : 2020 : On-line). Proceedings [recurso eletrônico]. São Paulo: ABMEC, 2020.
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