灰色预测方法在大城市时用水量预测中的研究

Study on forecasting of water demands based on grey theory in big city

分析了城市用水量预测的重要性和一些基本方法,发现灰色预测方法比传统的基于概率统计的随机过程分析具有建模所需信息少、不必知道原始数据分布的先验特征等优点,故将其尝试性的应用于城市时用水量的预测.通过对灰色预测方法建模机理的研究建立了城市用水量预测GM(1,1)模型,并以北方某大型城市时用水量为原始数据进行了实际预测,模型精度检验的结果表明该模型的预测等级为高精度预测.

The importance and some methods of water demands forecasting in cities are analyzed to find that the grey theory-based forecasting is better than conventional random analysis which is based on probability and statistics. The GM （1,1） model is established and applied to a practical project for hourly water demands forecasting. By checking up the precision, the model is proved to be feasible and effective.