The coal required quantity forecasting the method that before generally uses has analogy method,outside pushes method and cause effect analysis method etc, but the existing forecasting result precisionm is all lower.

Traditional analysis method is made a breakthrough in this paper,the coal required quantity evolution law is researched by means of chaos analysis.

A forecasting model for coal demand of China using a support vector regression was constructed.

Empirical analysis of Chinese coal policy and coal demand:1979—2005;

Affecting factors and projected scenarios for coal demand in China;

A superposition wavelet-neural network model of coal demand forecast;