(MDPI, 2023) García-Rodríguez, Sol; García-Rodríguez, Ana; Granados-López, D.; García Ruiz, Ignacio; Alonso-Tristán, Cristina; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC
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.
