Ultraviolet Erythemal Irradiance (UVER) under Different Sky Conditions in Burgos, Spain: Multilinear Regression and Artificial Neural Network Models

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 o...

Full description

Saved in:
Bibliographic Details
Published inApplied sciences Vol. 13; no. 19; p. 10979
Main Authors García-Rodríguez, S., García-Rodríguez, A., Granados-López, D., García, I., Alonso-Tristán, C.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.10.2023
Subjects
Algorithms
ANN
Erythema
Mathematical models
modeling
multilinear regression models
Neural networks
Quality control
Radiation
statistical analysis
ultraviolet erythemal irradiance
Ultraviolet radiation
UVER
Spain
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app131910979