Wind Speed Prediction Using OLS Algorithm based on RBF Neural Network

The growing revolution in wind energy encourages more accurate models for wind speed forecasting as the wind is fluctuate, periodic and volatile. An artificial neural network (ANN) method is used to predict the average hourly wind speed. Different from the multilayer perception network (MLP) which is more conversant, this paper presents a novel technique based on radial basis function (RBF) network using the orthogonal least-squares (OLS) algorithm, and also discusses how to organize the inputs of the network. The results reveal the effectiveness and accuracy of the proposed new approach to forecasting. Furthermore, the future work perspective is present at the end of this paper.