Electrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , |
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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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) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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