Supplementary data on monthly GSR model based on ANN: A case study in Spain

A monthly global solar radiation model based on a simple neural network structure, using temperature, geographical, and topographical data from 105 meteorological stations, representative of the whole of peninsular Spain has been developed. A hierarchical clustering procedure has been employed to select the data used to train and validate the model. To avoid functional dependencies between parameters and variables, which hinder the generality of the model, all input and output variables are dimensionless. The results of the model exceed those obtained in previous works using regression models and prove that the simplicity of a model is compatible with the generality and accuracy of its estimates even in large regions with very varied characteristics