基于偏回归平方和与多元回归的煤炭需求预测

Coal Demand Prediction Based on Partial Regression Square Sum and Multiple Regression

将偏回归平方和理论运用到影响煤炭需求量预测指标的选取中,确定了影响煤炭需求量预测的主要指标。根据这些指标建立了预测煤炭需求量的多元回归模型,并对预测结果作了分析,得出结论:采用偏回归平方和参数对全国煤炭需求量的影响因素进行优选而建立的多元回归模型,从总体上起到了提高预测精度的作用。用此方法进行预测是有效的,预测的结果是可信的。

This paper applied the theory of partial regression square sum into selecting the main prediction indexes which influence the coal demand. Based on these indexes,it presented a multiple regression model to forecast coal demand. It also made a discussion on the predictable result and draw a conclusion that the multiple regression model,which is set up through selecting the complications of influencing national coal demand with partial regression square sum parameter,plays a role in improving prediction accuracy on the whole. This method is effective, the predictable results are credible.