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.
