Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues

Detalhes bibliográficos
Autor(a) principal: Souza, A.
Data de Publicação: 2011
Outros Autores: Souza, F., Ferreira, N. B., Menezes, R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://ciencia.iscte-iul.pt/id/ci-pub-8276
http://hdl.handle.net/10071/13993
Resumo: The technique of forecast combination (FC) can achieve results superior to those generated by individual forecasting techniques. The purpose of this research is to present a method of FC based on the principal component analysis (PCA) applied to forecast values originating from individual forecasting models such as ARIMA, ARFIMA and SARIMA and their variants. From the PCA, it is possible to weigh up the values from each individual model in order to obtain a linear combination which represents all characteristics of valid models for each supplier. As an example, the FC method proposed was applied in the industrial sector of the three largest electric power suppliers in the State of Rio Grande do Sul, Brazil. The proposed method proved to be very useful since it presented better results than the individual models.
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spelling Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvaluesForecast combinationElectricity supply distributionForecastPrincipal component analysisThe technique of forecast combination (FC) can achieve results superior to those generated by individual forecasting techniques. The purpose of this research is to present a method of FC based on the principal component analysis (PCA) applied to forecast values originating from individual forecasting models such as ARIMA, ARFIMA and SARIMA and their variants. From the PCA, it is possible to weigh up the values from each individual model in order to obtain a linear combination which represents all characteristics of valid models for each supplier. As an example, the FC method proposed was applied in the industrial sector of the three largest electric power suppliers in the State of Rio Grande do Sul, Brazil. The proposed method proved to be very useful since it presented better results than the individual models.Departamento de Engenharia de Produção da Faculdade de Engenharia da UNESP2017-07-13T11:39:22Z2011-01-01T00:00:00Z20112017-07-13T11:37:49Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://ciencia.iscte-iul.pt/id/ci-pub-8276http://hdl.handle.net/10071/13993eng1984-2430Souza, A.Souza, F.Ferreira, N. B.Menezes, R.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:54:08Zoai:repositorio.iscte-iul.pt:10071/13993Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:27:14.580639Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
title Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
spellingShingle Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
Souza, A.
Forecast combination
Electricity supply distribution
Forecast
Principal component analysis
title_short Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
title_full Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
title_fullStr Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
title_full_unstemmed Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
title_sort Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
author Souza, A.
author_facet Souza, A.
Souza, F.
Ferreira, N. B.
Menezes, R.
author_role author
author2 Souza, F.
Ferreira, N. B.
Menezes, R.
author2_role author
author
author
dc.contributor.author.fl_str_mv Souza, A.
Souza, F.
Ferreira, N. B.
Menezes, R.
dc.subject.por.fl_str_mv Forecast combination
Electricity supply distribution
Forecast
Principal component analysis
topic Forecast combination
Electricity supply distribution
Forecast
Principal component analysis
description The technique of forecast combination (FC) can achieve results superior to those generated by individual forecasting techniques. The purpose of this research is to present a method of FC based on the principal component analysis (PCA) applied to forecast values originating from individual forecasting models such as ARIMA, ARFIMA and SARIMA and their variants. From the PCA, it is possible to weigh up the values from each individual model in order to obtain a linear combination which represents all characteristics of valid models for each supplier. As an example, the FC method proposed was applied in the industrial sector of the three largest electric power suppliers in the State of Rio Grande do Sul, Brazil. The proposed method proved to be very useful since it presented better results than the individual models.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01T00:00:00Z
2011
2017-07-13T11:39:22Z
2017-07-13T11:37:49Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ciencia.iscte-iul.pt/id/ci-pub-8276
http://hdl.handle.net/10071/13993
url https://ciencia.iscte-iul.pt/id/ci-pub-8276
http://hdl.handle.net/10071/13993
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1984-2430
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Departamento de Engenharia de Produção da Faculdade de Engenharia da UNESP
publisher.none.fl_str_mv Departamento de Engenharia de Produção da Faculdade de Engenharia da UNESP
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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