This paper studied the coal demand in the prediction accuracy problems. The traditional gray GM(1,1)model has the theoretical prediction problem of poor accuracy which leaded to less accurate prediction. A modified gray BP Neural Network forecasting model was used to predict the residual correction. The total consumption of coal as a major factor in variables was selected to construct forecast of coal demand The simulation results show that the proposed algorithm has better prediction accuracy and is an effective demand forecasting algorithm.
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