Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | GEPROS. Gestão da Produção. Operações e Sistemas |
Texto Completo: | https://revista.feb.unesp.br/gepros/article/view/597 |
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. Keywords: Forecast combination; electricity supply distribution; forecast; principal component analysis. |
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oai:ojs.gepros.emnuvens.com.br:article/597 |
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GEPROS. Gestão da Produção. Operações e Sistemas |
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Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvaluesThe 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. Keywords: Forecast combination; electricity supply distribution; forecast; principal component analysis.A Fundacao para o Desenvolvimento de Bauru (FunDeB)2012-03-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttps://revista.feb.unesp.br/gepros/article/view/59710.15675/gepros.v0i3.597Revista Gestão da Produção Operações e Sistemas; n. 3 (2011); 231984-2430reponame:GEPROS. Gestão da Produção. Operações e Sistemasinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporhttps://revista.feb.unesp.br/gepros/article/view/597/364https://revista.feb.unesp.br/gepros/article/view/597/1210https://revista.feb.unesp.br/gepros/article/view/597/1211https://revista.feb.unesp.br/gepros/article/view/597/1212Souza, Adriano MendonçaSouza, Francisca MendonçaFerreira, NunoMenezes, Ruiinfo:eu-repo/semantics/openAccess2012-03-12T19:41:52Zoai:ojs.gepros.emnuvens.com.br:article/597Revistahttps://revista.feb.unesp.br/geprosPUBhttps://revista.feb.unesp.br/gepros/oaigepros@feb.unesp.br||abjabbour@feb.unesp.br1984-24301809-614Xopendoar:2012-03-12T19:41:52GEPROS. Gestão da Produção. Operações e Sistemas - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
title |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
spellingShingle |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues Souza, Adriano Mendonça |
title_short |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
title_full |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
title_fullStr |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
title_full_unstemmed |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
title_sort |
Eletrical energy supply for Rio Grande do Sul, Brazil, using forecast combination of weighted eigenvalues |
author |
Souza, Adriano Mendonça |
author_facet |
Souza, Adriano Mendonça Souza, Francisca Mendonça Ferreira, Nuno Menezes, Rui |
author_role |
author |
author2 |
Souza, Francisca Mendonça Ferreira, Nuno Menezes, Rui |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Souza, Adriano Mendonça Souza, Francisca Mendonça Ferreira, Nuno Menezes, Rui |
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. Keywords: Forecast combination; electricity supply distribution; forecast; principal component analysis. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-03-04 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revista.feb.unesp.br/gepros/article/view/597 10.15675/gepros.v0i3.597 |
url |
https://revista.feb.unesp.br/gepros/article/view/597 |
identifier_str_mv |
10.15675/gepros.v0i3.597 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revista.feb.unesp.br/gepros/article/view/597/364 https://revista.feb.unesp.br/gepros/article/view/597/1210 https://revista.feb.unesp.br/gepros/article/view/597/1211 https://revista.feb.unesp.br/gepros/article/view/597/1212 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
A Fundacao para o Desenvolvimento de Bauru (FunDeB) |
publisher.none.fl_str_mv |
A Fundacao para o Desenvolvimento de Bauru (FunDeB) |
dc.source.none.fl_str_mv |
Revista Gestão da Produção Operações e Sistemas; n. 3 (2011); 23 1984-2430 reponame:GEPROS. Gestão da Produção. Operações e Sistemas instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
GEPROS. Gestão da Produção. Operações e Sistemas |
collection |
GEPROS. Gestão da Produção. Operações e Sistemas |
repository.name.fl_str_mv |
GEPROS. Gestão da Produção. Operações e Sistemas - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
gepros@feb.unesp.br||abjabbour@feb.unesp.br |
_version_ |
1800215695803285504 |