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

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

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dc.contributor.author Bas Cerdá, María del Carmen es_ES
dc.contributor.author Ortiz Moragón, Josefina es_ES
dc.contributor.author Ballesteros Pascual, Luisa es_ES
dc.contributor.author Martorell Alsina, Sebastián Salvador es_ES
dc.date.accessioned 2017-09-28T10:02:34Z
dc.date.available 2017-09-28T10:02:34Z
dc.date.issued 2017-06-01
dc.identifier.issn 0045-6535
dc.identifier.uri http://hdl.handle.net/10251/88143
dc.description.abstract [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. es_ES
dc.description.sponsorship 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. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation REM program of the Nuclear Safety Council of Spain (SRA/2071/2015/227.06) es_ES
dc.relation.ispartof Chemosphere es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject 7Be es_ES
dc.subject Time series es_ES
dc.subject Multiple linear regression es_ES
dc.subject Forecasting es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification INGENIERIA NUCLEAR es_ES
dc.title Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.chemosphere.2017.03.029
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2018-06-30 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Laboratorio de Radiactividad Ambiental - Laboratori de Radiactivitat Ambiental es_ES
dc.description.bibliographicCitation Bas Cerdá, MDC.; Ortiz Moragón, J.; Ballesteros Pascual, L.; Martorell Alsina, SS. (2017). Evaluation of a multiple linear regression model and SARIMA model in forecasting 7Be air concentrations. Chemosphere. 177:326-333. doi:10.1016/j.chemosphere.2017.03.029 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.chemosphere.2017.03.029 es_ES
dc.description.upvformatpinicio 326 es_ES
dc.description.upvformatpfin 333 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 177 es_ES
dc.relation.senia 329456 es_ES
dc.identifier.pmid 28319886


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