2026-04-28T00:11:20Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/62182024-05-14T10:46:56Zcom_10259_6231com_10259_4266com_10259.4_106com_10259_2604com_10259_6164com_10259_4534com_10259_6229com_10259_4393com_10259_5086col_10259_6232col_10259_6232col_10259_6165col_10259_6165col_10259_6230col_10259_6230col_10259_4394

García Rodríguez, Ana 214 600 0000-0003-3233-0525 Granados López, Diego 264 600 0000-0002-9046-7397 García Rodríguez, Sol 757 500 0000-0002-7064-0308 Diez Mediavilla, Montserrat 154 600 0000-0002-4957-9530 Alonso Tristán, Cristina 23 600 0000-0003-4733-7391 2021-11-24T08:10:34Z 2021-11-24T08:10:34Z 2021-11 0168-1923 http://hdl.handle.net/10259/6218 10.1016/j.agrformet.2021.108627 In 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. Regional 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). application/pdf eng Elsevier Agricultural and Forest Meteorology. 2021, V. 310, 108627 https://doi.org/10.1016/j.agrformet.2021.108627 info: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 fotovoltaica info: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 prevención info: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 BIOLOGICAS Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess PAR Modelling CIE standard sky classification Meteorología Electrotecnia Meteorology Electrical engineering Modelling Photosynthetic Active Radiation (PAR) through meteorological indices under all sky conditions info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion THUMBNAIL Garcia-afm_2021.pdf.jpg Garcia-afm_2021.pdf.jpg IM Thumbnail image/jpeg 5045 https://riubu.ubu.es/bitstream/10259/6218/4/Garcia-afm_2021.pdf.jpg 4313c6786fc14cc516bb55e511f0b328 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 999 https://riubu.ubu.es/bitstream/10259/6218/3/license.txt b295bcbce42e2caabeb0c623d3860c06 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 805 https://riubu.ubu.es/bitstream/10259/6218/2/license_rdf 4460e5956bc1d1639be9ae6146a50347 MD5 2 ORIGINAL Garcia-afm_2021.pdf Garcia-afm_2021.pdf application/pdf 3696556 https://riubu.ubu.es/bitstream/10259/6218/1/Garcia-afm_2021.pdf 5969b64400db7a1ddda21ecb859245f0 MD5 1 10259/6218 oai:riubu.ubu.es:10259/6218 2024-05-14 12:46:56.137 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es RWwgYXV0b3IgY29tbyDDum5pY28gdGl0dWxhciBkZSBsb3MgZGVyZWNob3MgZGUgcHJvcGllZGFkIGludGVsZWN0dWFsIGRlIGxhIG9icmEsIG8gZGlzcG9uaWVuZG8gZGUgbG9zIGRlYmlkb3MgcGVybWlzb3MgZGUgbG9zIG90cm9zIHRpdHVsYXJlcywgc2kgbG9zIGh1YmllcmEsIHkgZW4gdmlydHVkIGRlIGxvcyBkZXJlY2hvcyBxdWUgbGUgY29uZmllcmUgbGEgbGVnaXNsYWNpw7NuIHZpZ2VudGUgc29icmUgcHJvcGllZGFkIGludGVsZWN0dWFsIHkgZGVyZWNob3MgZGUgYXV0b3IsIA0KQVVUT1JJWkEgYSBsYSBVbml2ZXJzaWRhZCBkZSBCdXJnb3MgYSBkaWZ1bmRpciwgZGUgbWFuZXJhIGdyYXR1aXRhLCBlbCBjb250ZW5pZG8gZGUgbG9zIGFyY2hpdm9zIGRpZ2l0YWxlcyBxdWUgY29ycmVzcG9uZGVuIGFsIGRvY3VtZW50byBkZXNjcml0byBhbnRlcmlvcm1lbnRlLCBjb24gY2Fyw6FjdGVyIG5vIGV4Y2x1c2l2byB5IGRlIG1hbmVyYSBww7pibGljYSBlbiBhY2Nlc28gYWJpZXJ0byBhIHRyYXbDqXMgZGUgSW50ZXJuZXQsIHBhcmEgbG8gcXVlIGxhIEJpYmxpb3RlY2EgcHJvY2VkZXLDoSBhIGFyY2hpdmFybG9zIGVuIGVsIFJlcG9zaXRvcmlvIEluc3RpdHVjaW9uYWwuIEFzaW1pc21vIGF1dG9yaXphIGEgbGEgVW5pdmVyc2lkYWQgZGUgQnVyZ29zIGEgcmVhbGl6YXIgbGFzIHRyYW5zZm9ybWFjaW9uZXMgbmVjZXNhcmlhcyBkZSBmb3JtYXRvLCBubyBkZSBjb250ZW5pZG8sIHBhcmEgZ2FyYW50aXphciBsYSBwcmVzZXJ2YWNpw7NuIHkgZWwgYWNjZXNvIGVuIGVsIGZ1dHVyby4NCg0KRWwgYXV0b3IgZGlzcG9uZSwgZW4gdG9kbyBjYXNvLCBkZWwgZGVyZWNobyBhIHJldm9jYXIgZXN0YSBhdXRvcml6YWNpw7NuLg0KDQpMYSBjZXNpw7NuIGRlIGRlcmVjaG9zIGRlIGVzdGEgb2JyYSBzZSBlbmN1ZW50cmEgc3VqZXRhIGEgbGEgbGVnaXNsYWNpw7NuIHZpZ2VudGUgc29icmUgcHJvcGllZGFkIGludGVsZWN0dWFsIHkgZGVyZWNob3MgZGUgYXV0b3Iu