RT info:eu-repo/semantics/article
T1 Ultraviolet Erythemal Irradiance (UVER) under Different Sky Conditions in Burgos, Spain: Multilinear Regression and Artificial Neural Network Models
A1 García Rodríguez, Sol
A1 García Rodríguez, Ana
A1 Granados López, Diego
A1 García, Ignacio
A1 Alonso Tristán, Cristina
K1 Ultraviolet erythemal irradiance
K1 UVER
K1 Statistical analysis
K1 Modeling
K1 ANN
K1 Multilinear regression models
K1 Redes neuronales artificiales
K1 Neural networks (Computer science)
AB Different strategies for modeling Global Horizontal UltraViolet Erythemal irradiance (G⁡H⁡U⁢V⁢E) 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 (M⁢L⁢R) and artificial neural network (A⁢N⁢N) techniques were employed to model G⁡H⁡U⁢V⁢E under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the C⁢I⁢E standard on a 10 min basis. A⁢N⁢N models of G⁡H⁡U⁢V⁢E outperform those based on MLR according to the traditional statistical indices used in this study (R2, M⁢B⁢E, and n⁢R⁢M⁢S⁢E). Moreover, the work proposes a simple all-sky A⁢N⁢N model of G⁡H⁡U⁢V⁢E based on usually recorded variables at ground meteorological stations.
PB MDPI
YR 2023
FD 2023-10
LK https://hdl.handle.net/10259/11066
UL https://hdl.handle.net/10259/11066
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 01-may-2026