城市日用水量预测的组合动态建模方法

COMBINED DYNAMIC ALGORITHM OF DAILY URBAN WATER CONSUMPTION

本文根据城市用水量的影响因素及特点，利用统计预测理论，建立了日用水量的动态组合模型。通过逐步回归分析方法剔除次要影响因素，并采用卡尔曼滤波方法动态预测回归残差项。经沈阳市实例验证，该法预测误差小，可满足供水系统调度的实际需要。

In accordance with the influence factors and characteristics of the urban water consumption a combined dynamic algorithm model of daily urban water consumption has been established based on the statistic and predict theories. The sequential regression analysis was adopted to screen off the secondary factors, and the Kalman filtering technique was used to estimate innovation coefficients of the model dynamically. By the experiments at the Shenyang city, it was proved that the forecasting errors of the algorithm was little and can meet the practical requirement of water supply dispatch system.