Wind Speed Prediction Based on AdaBoost and BP Neural Networks
Hu-quan Guo · Power System and Clean Energy · 2012
This paper introduces an AdaBoost-based multi-neural network ensemble method for wind speed prediction.The result of the prediction by the ensemble method is theoretically and empirically proved to be superior to those by other methods.The AdaBoost algorithm is applied to the time series prediction.Based on the AdaBoost algorithm,back-propagation neural networks(BPNN) are generated;each for training on a random set of examples on wind speed data,then the results of each base learner will be combined to form the final hypothesis.The prediction error by this method is smaller than that by single BP neural network,and the analysis and simulation results suggest that the proposed approach results in better performance.