灰色递补模型在城市需水量预测中的应用

目的提出使用灰色递补模型准确地预测城市需水量,弥补传统灰色预测中不能对外界影响因素做出反应的不足.方法在传统灰色预测基础上,由已知数列预测一个值,将预测值补加到已知数列中去,同时去掉最早期的一个数据,保持维数的不变,接着预测下一个数据,把新的数据补充到原数列中去,同样去掉最早期的一个数据,这样逐个替换、补充,依次递补,直到完成预测目标.结果通过模型模拟结果可以看出灰色递补模型在模拟精度方面要远远超过传统灰色模型,灰色递补模型模拟的相对误差较小,小误差概率P、均方差比值C都较好,对未来需水量预测更准确.结论通过对比和实践验证,灰色递补模型弥补了传统灰色模型在预测中的不足,把外界对需水量的影响降到最低,能更好地预测城市未来需水量.

Application of Grey Information Renewal Model to the Forecast of City Water Requirement

The writers put forward the grey information renewal model in order to forecast city water requirement more accurately and to make up the insufficiency of traditional grey model in responding to the exterior influencing factors.Based on traditional grey forecast foundation and a value carried out by this forecast is added to the row of known numbers,at the same time,an earlier datum is removed and the dimension is maintained,then the next datum is foreseen.Add the new datum to the series again,and repeat the same steps until the forecast is finished .The result shows that the grey information renewal is better than traditional grey information with respect to precision.The small error probability P,mean-square deviation ratio C of the grey information model is better and the relative error of the gray information renewal model is smaller,so it will be more accurate when forecasting the future water demand.By comparison,grey information renewal model can modify the deficiency of traditional grey forecasting and foresee future water requirement accurately.