RT info:eu-repo/semantics/article
T1 Daily estimation of global solar irradiation and temperatures using artificial neural networks through the virtual weather station concept in Castilla and León, Spain
A1 Diez, Francisco Javier
A1 Boukharta, Ouiam Fatiha
A1 Navas Gracia, Luis Manuel
A1 Chico Santamarta, Leticia
A1 Martínez Rodríguez, Andrés
A1 Correa Guimaraes, Adriana
K1 Solar radiation
K1 Radiación solar
K1 Temperature measurements
K1 Meteorology
K1 Meteorology, Agricultural
K1 Evapotranspiration
K1 Evaporación (Meteorología) - España
K1 Climatology
K1 Artificial intelligence
K1 Redes neuronales (Informática)
K1 Spatial analysis (Statistics)
K1 Análisis espacial (Estadística)
K1 2509 Meteorología
K1 2509.01 Meteorología agrícola
K1 2502 Climatología
K1 1203.04 Inteligencia Artificial
AB In this article, the interpolation of daily data of global solar irradiation, and the maximum, average, and minimum temperatures were measured. These measurements were carried out in the agrometeorological stations belonging to the Agro-climatic Information System for Irrigation (SIAR, in Spanish) of the Region of Castilla and León, in Spain, through the concept of Virtual Weather Station (VWS), which is implemented with Artificial Neural Networks (ANNs). This is serving to estimate data in every point of the territory, according to their geographic coordinates (i.e., longitude and latitude). The ANNs of the Multilayer Feed-Forward Perceptron (MLP) used are daily trained, along with data recorded in 53 agro-meteorological stations, and where the validation of the results is conducted in the station of Tordesillas (Valladolid). The ANN models for daily interpolation were tested with one, two, three, and four neurons in the hidden layer, over a period of 15 days (from 1 to 15 June 2020), with a root mean square error (RMSE, MJ/m2) of 1.23, 1.38, 1.31, and 1.04, respectively, regarding the daily global solar irradiation. The interpolation of ambient temperature also performed well when applying the VWS concept, with an RMSE (°C) of 0.68 for the maximum temperature with an ANN of four hidden neurons, 0.58 for the average temperature with three hidden neurons, and 0.83 for the minimum temperature with four hidden neurons.
PB MDPI
SN 1424-8220
YR 2022
FD 2022
LK https://uvadoc.uva.es/handle/10324/61575
UL https://uvadoc.uva.es/handle/10324/61575
LA eng
NO Sensors, 2022, Vol. 22, Nº. 20, 7772
NO Producción Científica
DS UVaDOC
RD 28-nov-2024