Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations

[EN] Forecasting the 7Be air concentration is a target value in analyzing fluctuations that could reveal important information on the motions of atmospheric air masses. In this study we first propose a Seasonal Autoregressive Integrated Moving Average (SARIMA) model with a historical data time windo...

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Autores: Bas Cerdá, María del Carmen, Ortiz Moragón, Josefina, Ballesteros Pascual, Luisa|||0000-0001-8069-3086, Martorell Alsina, Sebastián Salvador|||0000-0003-1706-4740
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/88143
Acceso en línea:https://riunet.upv.es/handle/10251/88143
Access Level:acceso abierto
Palabra clave:7Be
Time series
Multiple linear regression
Forecasting
ESTADISTICA E INVESTIGACION OPERATIVA
INGENIERIA NUCLEAR
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spelling Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrationsBas Cerdá, María del CarmenOrtiz Moragón, JosefinaBallesteros Pascual, Luisa|||0000-0001-8069-3086Martorell Alsina, Sebastián Salvador|||0000-0003-1706-47407BeTime seriesMultiple linear regressionForecastingESTADISTICA E INVESTIGACION OPERATIVAINGENIERIA NUCLEAR[EN] Forecasting the 7Be air concentration is a target value in analyzing fluctuations that could reveal important information on the motions of atmospheric air masses. In this study we first propose a Seasonal Autoregressive Integrated Moving Average (SARIMA) model with a historical data time window of eight years (2007-2014) to forecast 7Be activity. The other proposal is a Multiple Linear Regression (MLR) model for the same time period, in which the atmospheric and meteorological variables are used to forecast 7Be air concentrations. The forecasting performance of both models is evaluated by comparison with real 7Be air concentrations by out-of-sample tests for the 12 months of the year 2015. Considering the high explicative power and the consistently low accuracy of the measurements in the out-of-sample year, the proposed SARIMA model provides good forecasts of 7Be air concentrations. In contrast, the MLR model provides information on the significant meteorological variables that affect 7Be concentrations and could be useful to identify meteorological or atmospheric changes that could cause deviations in these concentrations.This study has been partially supported by the REM program of the Nuclear Safety Council of Spain (SRA/2071/2015/227.06). We are also grateful to the UPV's weather station for providing the atmospheric information used in this study.ElsevierDepartamento de Ingeniería Química y NuclearEscuela Técnica Superior de Ingeniería IndustrialGrupo de Medioambiente y Seguridad Industrial. MEDASEGIConsejo de Seguridad NuclearRepositorio Institucional de la Universitat Politècnica de València Riunet20172017-06-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/88143reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengConsejo de Seguridad Nuclear https://doi.org/10.13039/501100006055 SRA%2F2071%2F2015%2F227.06open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/881432026-06-13T07:49:27Z
dc.title.none.fl_str_mv Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
title Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
spellingShingle Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
Bas Cerdá, María del Carmen
7Be
Time series
Multiple linear regression
Forecasting
ESTADISTICA E INVESTIGACION OPERATIVA
INGENIERIA NUCLEAR
title_short Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
title_full Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
title_fullStr Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
title_full_unstemmed Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
title_sort Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations
dc.creator.none.fl_str_mv Bas Cerdá, María del Carmen
Ortiz Moragón, Josefina
Ballesteros Pascual, Luisa|||0000-0001-8069-3086
Martorell Alsina, Sebastián Salvador|||0000-0003-1706-4740
author Bas Cerdá, María del Carmen
author_facet Bas Cerdá, María del Carmen
Ortiz Moragón, Josefina
Ballesteros Pascual, Luisa|||0000-0001-8069-3086
Martorell Alsina, Sebastián Salvador|||0000-0003-1706-4740
author_role author
author2 Ortiz Moragón, Josefina
Ballesteros Pascual, Luisa|||0000-0001-8069-3086
Martorell Alsina, Sebastián Salvador|||0000-0003-1706-4740
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Química y Nuclear
Escuela Técnica Superior de Ingeniería Industrial
Grupo de Medioambiente y Seguridad Industrial. MEDASEGI
Consejo de Seguridad Nuclear
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv 7Be
Time series
Multiple linear regression
Forecasting
ESTADISTICA E INVESTIGACION OPERATIVA
INGENIERIA NUCLEAR
topic 7Be
Time series
Multiple linear regression
Forecasting
ESTADISTICA E INVESTIGACION OPERATIVA
INGENIERIA NUCLEAR
description [EN] Forecasting the 7Be air concentration is a target value in analyzing fluctuations that could reveal important information on the motions of atmospheric air masses. In this study we first propose a Seasonal Autoregressive Integrated Moving Average (SARIMA) model with a historical data time window of eight years (2007-2014) to forecast 7Be activity. The other proposal is a Multiple Linear Regression (MLR) model for the same time period, in which the atmospheric and meteorological variables are used to forecast 7Be air concentrations. The forecasting performance of both models is evaluated by comparison with real 7Be air concentrations by out-of-sample tests for the 12 months of the year 2015. Considering the high explicative power and the consistently low accuracy of the measurements in the out-of-sample year, the proposed SARIMA model provides good forecasts of 7Be air concentrations. In contrast, the MLR model provides information on the significant meteorological variables that affect 7Be concentrations and could be useful to identify meteorological or atmospheric changes that could cause deviations in these concentrations.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-06-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/88143
url https://riunet.upv.es/handle/10251/88143
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Consejo de Seguridad Nuclear https://doi.org/10.13039/501100006055 SRA%2F2071%2F2015%2F227.06
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300724

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