Abstract:
The present work investigates the potential of artificial neural network (ANN) model to predict the
horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years
meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1
university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal
configuration of the ANN model has been determined by minimizing the Root Means Square Error
(RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the
ANN model. To select the best ANN architecture, we have conducted several tests by using different
combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an
optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was
designed based on the best network structure and training algorithm, to enhance the users’ friendliness
application of the model
