2026-06-29T23:01:34Zhttps://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

00925njm 22002777a 4500 dc Dieste Velasco, Mª Isabel author García Rodríguez, Sol author García Rodríguez, Ana author Diez Mediavilla, Montserrat author Alonso Tristán, Cristina author 2023-01 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. http://hdl.handle.net/10259/7537 10.3390/app13031473 2076-3417 UV irradiance ANN Modeling Multilinear regression models Modeling Horizontal Ultraviolet Irradiance for All Sky Conditions by Using Artificial Neural Networks and Regression Models