Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | BBR. Brazilian Business Review (English edition. Online) |
Texto Completo: | http://www.bbronline.com.br/index.php/bbr/article/view/302 |
Resumo: | An important economic activity in any society regards the commercialization of assets. The retail consists exactly of the link established between the industry and the final consumer. To predict the sales is essential so that one can manage in a proper way the production and commercialization processes. In the retail, this aspect is even more important. To sale means to harmonize the concerns of those producing with those who buy. Therefore, this paper is intended to exam comparatively the application of two retail sales forecast methods in the Brazilian market: the temporal series and the neural networks. The selection of those two techniques as object of that comparison was aroused by the importance those two conceptions have assumed in the literature. Although the utilization of neural networks has provided the smallest sum of the squares of the residues, one may say that the results using models of the ARIMA type have shown to be practically equivalent. |
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BBR. Brazilian Business Review (English edition. Online) |
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Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecastSéries temporais e redes neurais: uma análise comparativa de técnicas na previsão de vendas do varejo brasileiroTemporal seriesneural networkssales forecastretailSéries temporaisredes neuraisprevisão de vendasvarejoAn important economic activity in any society regards the commercialization of assets. The retail consists exactly of the link established between the industry and the final consumer. To predict the sales is essential so that one can manage in a proper way the production and commercialization processes. In the retail, this aspect is even more important. To sale means to harmonize the concerns of those producing with those who buy. Therefore, this paper is intended to exam comparatively the application of two retail sales forecast methods in the Brazilian market: the temporal series and the neural networks. The selection of those two techniques as object of that comparison was aroused by the importance those two conceptions have assumed in the literature. Although the utilization of neural networks has provided the smallest sum of the squares of the residues, one may say that the results using models of the ARIMA type have shown to be practically equivalent.Uma importante atividade econômica em qualquer sociedade diz respeito à comercialização de bens. O varejo consiste exatamente no vínculo que se estabelece entre a indústria e o consumidor final. Prever as vendas é essencial para que se possa gerenciar de modo adequado os processos produtivos e de comercialização. No varejo esse aspecto reveste-se de importância ainda maior. Vender significa harmonizar os interesses dos que produzem com aqueles que compram. Portanto, o presente trabalho tem por propósito examinar comparativamente dois métodos de previsão: as séries temporais e as redes neurais. A escolha dessas duas técnicas como objeto dessa comparação foi suscitada pela importância que essas duas concepções têm assumido na literatura. Embora a utilização de redes neurais tenha proporcionado a menor soma dos quadrados dos resíduos, pode-se dizer que os resultados empregando modelos do tipo ARIMA se mostraram praticamente equivalentes.FUCAPE Business Shool2011-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed ArticleArtigo revisado pelos paresapplication/pdfapplication/pdfhttp://www.bbronline.com.br/index.php/bbr/article/view/30210.15728/bbr.2011.8.2.1Brazilian Business Review; Vol. 8 No. 2 (2011): April to June 2011; 1-21Brazilian Business Review; v. 8 n. 2 (2011): Abril a Junho de 2011; 1-211808-23861807-734Xreponame:BBR. Brazilian Business Review (English edition. Online)instname:Fucape Business School (FBS)instacron:FBSengporhttp://www.bbronline.com.br/index.php/bbr/article/view/302/455http://www.bbronline.com.br/index.php/bbr/article/view/302/456Angelo, Claudio Felisoni deZwicker, RonaldoFouto, Nuno Manoel Martins DiasLuppe, Marcos Robertoinfo:eu-repo/semantics/openAccess2018-11-06T19:56:07Zoai:ojs.pkp.sfu.ca:article/302Revistahttps://www.bbronline.com.br/index.php/bbr/indexONGhttp://www.bbronline.com.br/index.php/bbr/oai|| bbronline@bbronline.com.br1808-23861808-2386opendoar:2018-11-06T19:56:07BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)false |
dc.title.none.fl_str_mv |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast Séries temporais e redes neurais: uma análise comparativa de técnicas na previsão de vendas do varejo brasileiro |
title |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
spellingShingle |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast Angelo, Claudio Felisoni de Temporal series neural networks sales forecast retail Séries temporais redes neurais previsão de vendas varejo |
title_short |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
title_full |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
title_fullStr |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
title_full_unstemmed |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
title_sort |
Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast |
author |
Angelo, Claudio Felisoni de |
author_facet |
Angelo, Claudio Felisoni de Zwicker, Ronaldo Fouto, Nuno Manoel Martins Dias Luppe, Marcos Roberto |
author_role |
author |
author2 |
Zwicker, Ronaldo Fouto, Nuno Manoel Martins Dias Luppe, Marcos Roberto |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Angelo, Claudio Felisoni de Zwicker, Ronaldo Fouto, Nuno Manoel Martins Dias Luppe, Marcos Roberto |
dc.subject.por.fl_str_mv |
Temporal series neural networks sales forecast retail Séries temporais redes neurais previsão de vendas varejo |
topic |
Temporal series neural networks sales forecast retail Séries temporais redes neurais previsão de vendas varejo |
description |
An important economic activity in any society regards the commercialization of assets. The retail consists exactly of the link established between the industry and the final consumer. To predict the sales is essential so that one can manage in a proper way the production and commercialization processes. In the retail, this aspect is even more important. To sale means to harmonize the concerns of those producing with those who buy. Therefore, this paper is intended to exam comparatively the application of two retail sales forecast methods in the Brazilian market: the temporal series and the neural networks. The selection of those two techniques as object of that comparison was aroused by the importance those two conceptions have assumed in the literature. Although the utilization of neural networks has provided the smallest sum of the squares of the residues, one may say that the results using models of the ARIMA type have shown to be practically equivalent. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Artigo revisado pelos pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.bbronline.com.br/index.php/bbr/article/view/302 10.15728/bbr.2011.8.2.1 |
url |
http://www.bbronline.com.br/index.php/bbr/article/view/302 |
identifier_str_mv |
10.15728/bbr.2011.8.2.1 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
http://www.bbronline.com.br/index.php/bbr/article/view/302/455 http://www.bbronline.com.br/index.php/bbr/article/view/302/456 |
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 |
dc.publisher.none.fl_str_mv |
FUCAPE Business Shool |
publisher.none.fl_str_mv |
FUCAPE Business Shool |
dc.source.none.fl_str_mv |
Brazilian Business Review; Vol. 8 No. 2 (2011): April to June 2011; 1-21 Brazilian Business Review; v. 8 n. 2 (2011): Abril a Junho de 2011; 1-21 1808-2386 1807-734X reponame:BBR. Brazilian Business Review (English edition. Online) instname:Fucape Business School (FBS) instacron:FBS |
instname_str |
Fucape Business School (FBS) |
instacron_str |
FBS |
institution |
FBS |
reponame_str |
BBR. Brazilian Business Review (English edition. Online) |
collection |
BBR. Brazilian Business Review (English edition. Online) |
repository.name.fl_str_mv |
BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS) |
repository.mail.fl_str_mv |
|| bbronline@bbronline.com.br |
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