Wind Speed Prediction Using Artificial Neural Networks

Abstract

A multilayered artificial neural network has been used for predicting the mean monthly wind speed in regions of Cyprus where data are not available. Data for the period 1986-1996 have been used to train a neural network, whereas data for the year 1997 were used for validation. Both learning and prediction were performed with adequate accuracy. Two network architectures of the similar type have been tried. One with eleven neurons in the input layer and one with five. The second one proved to be more accurate in predicting the mean wind speed. The maximum percentage difference for the validation set was confined to less than 1.8% on an annual basis, which is considered by the domain expert as adequate.