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dc.contributor.authorCrespo Turrado, Concepción
dc.contributor.authorMeizoso-López, María-Carmen
dc.contributor.authorSánchez Lasheras, Fernando
dc.contributor.authorRodríguez Gómez, Benigno Antonio
dc.contributor.authorCalvo-Rolle, José Luis
dc.contributor.authorCos Juez, Francisco Javier de
dc.date2014
dc.date.accessioned2017-04-26T18:35:44Z
dc.date.available2017-04-26T18:35:44Z
dc.date.issued2014
dc.identifier.citationTurrado, C.C.; López, M.C.M.; Lasheras, F.S.; Gómez, B.A.R.; Rollé, J.L.C.; Juez, F.J.C. Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions. Sensors 2014, 14, 20382-20399.es_ES
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2183/18458
dc.description.abstractGlobal solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.es_ES
dc.description.sponsorshipMinisterio de Economía, Industria y Competitividad; AYA2010-18513es_ES
dc.language.isoenges_ES
dc.publisherMultidisciplinary Digital Publishing Institutees_ES
dc.relation.urihttp://dx.doi.org/10.3390/s141120382es_ES
dc.rightsReconocimiento 3.0es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/
dc.subjectMissing data imputationes_ES
dc.subjectMultivariate imputation by chained equations (mice)es_ES
dc.subjectMultiple linear regressiones_ES
dc.subjectSolar radiationes_ES
dc.subjectPyranometeres_ES
dc.titleMissing Data Imputation of Solar Radiation Data under Different Atmospheric Conditionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleSensorses_ES
UDC.volume14es_ES
UDC.issue11es_ES
UDC.startPage20382es_ES
UDC.endPage20399es_ES


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