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dc.contributor.authorGarcía Rodríguez, Ana 
dc.contributor.authorGranados López, Diego 
dc.contributor.authorGarcía Rodríguez, Sol 
dc.contributor.authorDiez Mediavilla, Montserrat 
dc.contributor.authorAlonso Tristán, Cristina 
dc.date.accessioned2021-11-24T08:10:34Z
dc.date.available2021-11-24T08:10:34Z
dc.date.issued2021-11
dc.identifier.issn0168-1923
dc.identifier.urihttp://hdl.handle.net/10259/6218
dc.description.abstractIn this study, ten-minute meteorological data-sets recorded at Burgos, Spain, are used to develop models of Photosynthetic Active Radiation () following two different procedures: multilinear regression and Artificial Neural Networks. Ten Meteorological Indices (MIs) are chosen as inputs to the models: clearness index (), diffuse fraction (), direct fraction (), Perez's clear sky index (ɛ), brightness index (), cloud cover (), air temperature (), pressure (), solar azimuth cosine (), and horizontal global irradiation (). The experimental data are clustered according to the sky conditions, following the CIE standard sky classification. A previous feature selection procedure established the most adequate MIs for modelling in clear, partial and overcast sky conditions. was the common MI used by all models and for all sky conditions. Additional variables were also included: the geometrical parameter, , and three variables related to the sky conditions, , and Both modelling methods, multilinear regression and ANN, yielded very high determination coefficients () with very close results in the models for each of the different sky conditions. Slight improvements can be observed in the ANN models. The results underline the equivalence of multilinear regression models and ANN models of PAR following previous feature selection procedures.en
dc.description.sponsorshipRegional Government of Castilla y León, under projects BU021G19 and INVESTUN/19/BU/0004 and the Spanish Ministry of Science & Innovation under the I+D +i state program “Challenges Research Projects” (Ref. RTI2018-098900-B-I00). Diego Granados López expresses his thanks to the Junta de Castilla y León for economic support (PIRTU Program, ORDEN EDU/556/2019).en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofAgricultural and Forest Meteorology. 2021, V. 310, 108627en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPARen
dc.subjectModellingen
dc.subjectCIE standard sky classificationen
dc.subject.otherMeteorologíaes
dc.subject.otherMeteorologyen
dc.subject.otherIngeniería eléctricaes
dc.subject.otherElectric engineeringen
dc.titleModelling Photosynthetic Active Radiation (PAR) through meteorological indices under all sky conditionsen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1016/j.agrformet.2021.108627es
dc.identifier.doi10.1016/j.agrformet.2021.108627
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//BU021G19//Metodología para la rehabilitación energética de edificios de uso público en castilla y león mediante integración fotovoltaicaes
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//INVESTUN%2F19%2FBU%2F0004//Valoración técnica de los niveles de exposición a radiación solar en trabajos de exterior: identificación de grupos de riesgo y medidas de prevenciónes
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098900-B-I00/ES/ANALISIS ESPECTRAL DE LA RADIACION SOLAR: APLICACIONES CLIMATICAS, ENERGETICAS Y BIOLOGICASes
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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