人工神经网络法预测城市用水量

城市用水量的预测结果，对于城市规划、供水系统的管理及改扩建有着重要的意义，寻求科学合理的预测模型是保障预测结果准确可靠的关键。针对这一问题，利用人工神经网络理论建立了BP（Back—Propagation，反向传播算法）网络预测模型，该模型考虑了反映社会、经济的两个影响因素人口和工业产值对用水量需求的影响，具备系统决策功能。通过实例证明该模型是一种行之有效的用水量预测模型。

Forecast model for urban water demand using artificial neural network

It is of great significance for city planning and management of water supply system to forecast urban water demand, and the key to accurate forecast is to find out scientific and reasonable forecast model. A BP forecast model therefore is built using the artificial neural network theory. The model included the influences of two factors to urban water demand, the population and the industrial production value reflecting society and economics respectively. The proposed forecasting model has systematic decision-making function. Typical examples proved that the model is a very accurate water demand forecast model.