Using Wavelet Transform And Neural Network Algorithm For Power Demand Prediction
نویسندگان
چکیده
This paper presents a method for prediction short-term power demand of a vehicular power system. The forecasting of power demand is presented using wavelet decomposition and artificial neural network, a hybrid model which absorbs some merits of wavelet transform and neural network. The power demand time series is first decomposed into a certain number of levels with discreet wavelet transform and for each individual wavelet sub-series are created neural networks to predict future values. To form the aggregate prediction the individual wavelet sub-series forecasts are recombined utilizing the reconstruction property of wavelet transform. The results are conducted in Matlab software and the performance of this procedure is investigated.
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