Ultraviolet erythemal irradiance (UVER) under different sky conditions in Burgos, Spain: multilinear regression and artificial neural network models
| dc.contributor.author | García-Rodríguez, Sol | |
| dc.contributor.author | García-Rodríguez, Ana | |
| dc.contributor.author | Granados-López, D. | |
| dc.contributor.author | García Ruiz, Ignacio | |
| dc.contributor.author | Alonso-Tristán, Cristina | |
| dc.contributor.department | Ingeniería | es_ES |
| dc.contributor.department | Ingeniaritza | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.date.accessioned | 2024-02-21T13:00:57Z | |
| dc.date.available | 2024-02-21T13:00:57Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2024-02-21T12:38:07Z | |
| dc.description.abstract | Different strategies for modeling Global Horizontal UltraViolet Erythemal irradiance (GHUVE) based on meteorological parameters measured in Burgos (Spain) have been developed. The experimental campaign ran from September 2020 to June 2022. The selection of relevant variables for modeling was based on Pearson’s correlation coefficient. Multilinear Regression Model (MLR) and artificial neural network (ANN) techniques were employed to model GHUVE under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the CIE standard on a 10 min basis. ANN models of GHUVE outperform those based on MLR according to the traditional statistical indices used in this study (R2, MBE, and nRMSE). Moreover, the work proposes a simple all-sky ANN model of GHUVE based on usually recorded variables at ground meteorological stations. | es_ES |
| dc.description.sponsorship | This research was funded by MCIN/AEI/ 10.13039/501100011033 and the “European Union Next Generation EU/PRTR grant numbers TED2021-131563B-I00 and PID2022-139477OB-I00 and Junta de Castilla y León, grant number INVESTUN/19/BU/0004. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | García-Rodríguez, S., García-Rodríguez, A., Granados-López, D., García, I., Alonso-Tristán, C. (2023) Ultraviolet Erythemal Irradiance (UVER) under different sky conditions in Burgos, Spain: Multilinear regression and artificial neural network models. Applied Sicences, 13(19), 1-16. https://doi.org/10.3390/app131910979. | es_ES |
| dc.identifier.doi | 10.3390/app131910979 | |
| dc.identifier.issn | 2076-3417 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/47534 | |
| dc.language.iso | eng | en |
| dc.publisher | MDPI | en |
| dc.relation.ispartof | Applied Sciences 2023, 13, 10979 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI//TED2021-131563B-I00/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-139477OB-I00/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.3390/app131910979 | |
| dc.rights | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Ultraviolet erythemal irradiance | en |
| dc.subject | UVER | en |
| dc.subject | Statistical analysis | en |
| dc.subject | Modeling | en |
| dc.subject | ANN | en |
| dc.subject | Multilinear regression models | en |
| dc.title | Ultraviolet erythemal irradiance (UVER) under different sky conditions in Burgos, Spain: multilinear regression and artificial neural network models | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | dcdadcc0-60de-44b9-8af5-c2c523c90d95 | |
| relation.isAuthorOfPublication.latestForDiscovery | dcdadcc0-60de-44b9-8af5-c2c523c90d95 |