2026-04-17T13:22:25Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/72372024-05-14T10:09:05Zcom_10259_6229com_10259_4534com_10259.4_106com_10259_2604com_10259_6231com_10259_4266com_10259_4393com_10259_5086col_10259_6230col_10259_6232col_10259_4394

García Rodríguez, Ana 214 600 0000-0003-3233-0525 García Rodríguez, Sol 757 600 0000-0002-7064-0308 Granados López, Diego 264 600 0000-0002-9046-7397 Diez Mediavilla, Montserrat 154 600 0000-0002-4957-9530 Alonso Tristán, Cristina 23 600 0000-0003-4733-7391 2023-01-13T11:25:47Z 2023-01-13T11:25:47Z 2022-03 2076-3417 http://hdl.handle.net/10259/7237 10.3390/app12052372 2076-3417 Four models for predicting Photosynthetically Active Radiation (PAR) were obtained through MultiLinear Regression (MLR) and an Artificial Neural Network (ANN) based on 10 meteorological indices previously selected from a feature selection algorithm. One model was developed for all sky conditions and the other three for clear, partial, and overcast skies, using a sky classification based on the clearness index (kt). The experimental data were recorded in Burgos (Spain) at ten-minute intervals over 23 months between 2019 and 2021. Fits above 0.97 and Root Mean Square Error (RMSE) values below 7.5% were observed. The models developed for clear and overcast sky conditions yielded better results. Application of the models to the seven experimental ground stations that constitute the Surface Radiation Budget Network (SURFRAD) located in different Köppen climatic zones of the USA yielded fitted values higher than 0.98 and RMSE values less than 11% in all cases regardless of the sky type. This research was funded by the Spanish Ministry of Science and Innovation, grant number RTI2018-098900-B-I00, and Consejería de Empleo e Industria, Junta de Castilla y León, grant number INVESTUN/19/BU-0004. application/pdf eng MDPI Applied Sciences. 2022, V. 12, n. 5, 2372 https://doi.org/10.3390/app12052372 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 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 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Photosynthetically active radiation kt sky classification ANN Multilinear regression models Electrotecnia Electrical engineering Extension of PAR Models under Local All-Sky Conditions to Different Climatic Zones info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Applied Sciences 12 5 2372 THUMBNAIL Garcia-as_2022.pdf.jpg Garcia-as_2022.pdf.jpg IM Thumbnail image/jpeg 3424 https://riubu.ubu.es/bitstream/10259/7237/4/Garcia-as_2022.pdf.jpg 015ffeaf0e2b5bb6969c0182502757de MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 999 https://riubu.ubu.es/bitstream/10259/7237/3/license.txt b295bcbce42e2caabeb0c623d3860c06 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 908 https://riubu.ubu.es/bitstream/10259/7237/2/license_rdf 0175ea4a2d4caec4bbcc37e300941108 MD5 2 ORIGINAL Garcia-as_2022.pdf Garcia-as_2022.pdf application/pdf 3933833 https://riubu.ubu.es/bitstream/10259/7237/1/Garcia-as_2022.pdf 12c812014dccea6f32da975854acb99a MD5 1 10259/7237 oai:riubu.ubu.es:10259/7237 2024-05-14 12:09:05.222 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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