This study explores the possibility of developing an artificial neural networks model that could be used to predict monthly average daily total solar irradiation on a horizontal surface for locations in Uganda based on geographical and meteorological data: latitude, longitude, altitude, sunshine...

In this work, a novel approach using an artificial neural network was used to develop a model for analyzing the relationship between the Global Radiation (GR) and climatological variables, and to predict GR for locations not covered by the model's training data. The predicted global radiation...

In this paper, a genetic approach combing multi-model framework for solar radiation time series prediction is proposed. The framework starts with the assumption that there exists several different patterns in the stochastic component of the solar radiation series. To uncover the underlying...

In this paper, Radial Basis Function network (RBF) is used for modelling and predicting the daily global solar radiation data using other meteorological data such as air temperature, sunshine duration, and relative humidity. These data were recorded in the period 1998–2002 at Al-Madinah (Saudi...