Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case

Time series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANN’s parameters. In this work a method based on statistical analysis and optimization...

Descripción completa

Detalles Bibliográficos
Autores: María Angélica Salazar Aguilar, Guillermo J. Moreno Rodríguez, Mauricio Cabrera-Ríos
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2006
País:México
Institución:Universidad Autónoma de Nuevo León
Repositorio:Redalyc-UANL
OAI Identifier:oai:redalyc.org:61501106
Acceso en línea:https://www.redalyc.org/articulo.oa?id=61501106
Access Level:acceso abierto
Palabra clave:Computación
Time Series Forecasting
Artificial Neural Networks
Design and Analysis of Experiments
id MX_8ba04f69964f587e05c66a7b1d4149d0
oai_identifier_str oai:redalyc.org:61501106
network_acronym_str MX
network_name_str México
repository_id_str
spelling Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast caseMaría Angélica Salazar AguilarGuillermo J. Moreno RodríguezMauricio Cabrera-RíosComputaciónTime Series ForecastingArtificial Neural NetworksDesign and Analysis of ExperimentsTime series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANN’s parameters. In this work a method based on statistical analysis and optimization techniques is proposed to select the ANN´s parameters for application in time series forecasting. The results on the successful application of the method in a real demand forecasting problem for the telecommunications industry are also reported. .Instituto Politécnico Nacional2006info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf1405-5546https://www.redalyc.org/articulo.oa?id=61501106Computación y Sistemas (México) Num.1 Vol.10reponame:Redalyc-UANLinstname:Universidad Autónoma de Nuevo Leóninstacron:UANLenhttp://www.redalyc.org/revista.oa?id=615Computación y Sistemasinfo:eu-repo/semantics/openAccessoai:redalyc.org:615011062024-08-23T15:25:13Z
dc.title.none.fl_str_mv Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
title Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
spellingShingle Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
María Angélica Salazar Aguilar
Computación
Time Series Forecasting
Artificial Neural Networks
Design and Analysis of Experiments
title_short Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
title_full Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
title_fullStr Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
title_full_unstemmed Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
title_sort Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case
dc.creator.none.fl_str_mv María Angélica Salazar Aguilar
Guillermo J. Moreno Rodríguez
Mauricio Cabrera-Ríos
author María Angélica Salazar Aguilar
author_facet María Angélica Salazar Aguilar
Guillermo J. Moreno Rodríguez
Mauricio Cabrera-Ríos
author_role author
author2 Guillermo J. Moreno Rodríguez
Mauricio Cabrera-Ríos
author2_role author
author
dc.subject.none.fl_str_mv Computación
Time Series Forecasting
Artificial Neural Networks
Design and Analysis of Experiments
topic Computación
Time Series Forecasting
Artificial Neural Networks
Design and Analysis of Experiments
description Time series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANN’s parameters. In this work a method based on statistical analysis and optimization techniques is proposed to select the ANN´s parameters for application in time series forecasting. The results on the successful application of the method in a real demand forecasting problem for the telecommunications industry are also reported. .
publishDate 2006
dc.date.none.fl_str_mv 2006
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 1405-5546
https://www.redalyc.org/articulo.oa?id=61501106
identifier_str_mv 1405-5546
url https://www.redalyc.org/articulo.oa?id=61501106
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv http://www.redalyc.org/revista.oa?id=615
dc.rights.none.fl_str_mv Computación y Sistemas
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Computación y Sistemas
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Politécnico Nacional
publisher.none.fl_str_mv Instituto Politécnico Nacional
dc.source.none.fl_str_mv Computación y Sistemas (México) Num.1 Vol.10
reponame:Redalyc-UANL
instname:Universidad Autónoma de Nuevo León
instacron:UANL
instname_str Universidad Autónoma de Nuevo León
instacron_str UANL
institution UANL
reponame_str Redalyc-UANL
collection Redalyc-UANL
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1858176047432859648
score 15,811543

Similares en LA Referencia