Prediction of global solar radiation in UAE using artificial neural networks

This paper presents an artificial neural network (ANN) model for predication global solar radiation (GSR) for main cities in the UAE namely, Abu Dhabi, Al-Ain and Dubai. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) techniques with comprehensive training algorithms, architectures, and different combinations of inputs are used to develop these models. The measured data include the maximum temperature (°C), mean wind speed (knot), sunshine hours, mean relative humidity (%) and mean daily global solar radiation on a horizontal surface (kWh/m²). This data was provided by the National Center of Meteorology and Seismology (NCMS) of Abu Dhabi. The results show the generalization capability of ANN approach and its ability to generate accurate prediction of GSR in UAE.