2026-06-29T20:30:11Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/75372024-05-14T10:45:28Zcom_10259_6229com_10259_4534com_10259.4_106com_10259_2604com_10259_4393com_10259_5086col_10259_6230col_10259_4394

Dieste Velasco, Mª Isabel García Rodríguez, Sol García Rodríguez, Ana Diez Mediavilla, Montserrat Alonso Tristán, Cristina 2023-03-13T12:15:46Z 2023-03-13T12:15:46Z 2023-01 http://hdl.handle.net/10259/7537 10.3390/app13031473 2076-3417 In the present study, different models constructed with meteorological variables are proposed for the determination of horizontal ultraviolet irradiance (IUV), on the basis of data collected at Burgos (Spain) during an experimental campaign between March 2020 and May 2022. The aim is to explore the effectiveness of a range of variables for modelling horizontal ultraviolet irradiance through a comparison of supervised artificial neural network (ANN) and regression model results. A preliminary feature selection process using the Pearson correlation coefficient was sufficient to determine the variables for use in the models. The following variables and their influence on horizontal ultraviolet irradiance were analyzed: horizontal global irradiance (IGH), clearness index (kt), solar altitude angle (α), horizontal beam irradiance (IBH), diffuse fraction (D), temperature (T), sky clearness (ε), cloud cover (Cc), horizontal diffuse irradiance (IDH), and sky brightness (∆). The ANN models yielded results of greater accuracy than the regression models. eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional UV irradiance ANN Modeling Multilinear regression models Modeling Horizontal Ultraviolet Irradiance for All Sky Conditions by Using Artificial Neural Networks and Regression Models info:eu-repo/semantics/article