基于GA-BP神经网络的城市用水量预测

Urban water consumption prediction based on GA-BP neural network

城市用水准确的预测结果,对城市供水系统的控制具有直接的影响,而良好的城市用水控制系统不仅能够提高城市各个时段的供水效率,而且对城市人民生活幸福指数有较高的影响。该文设计通过分析传统的BP神经网络对城市用水量预测容易陷入局部误差极小,预测结果存在一定误差,提出在BP神经网络的基础上通过遗传算法优化BP神经网络进行城市用水量预测。通过设计GA-BP神经网络的具体结构,对已知的城市每日时用水量数据进行网络训练和学习。结果显示该模型具有一定的精度和适用性,预测结果可用于城市供水优化调度模型。

The accurate prediction of urban water usage has a direct impact on the control of urban water-supply system.The good urban water control system can not only improve the water-supply efficiency in every time bucket of the city,but also have a serious impact on the urban people′s life happiness index. On the basis of the analysis that the traditional BP neural network is easy to fall into the local error minimum in the prediction of urban water consumption,and the prediction results has a certain error,the urban water consumption prediction based on BP neural network optimized by genetic algorithm is proposed.The specific structure of GA-BP neural network is designed to perform the network training and learning of known data of water consumption per hour in a city. The results show that the model has a certain accuracy and applicability,and the prediction results can be used in the urban water-supply optimization scheduling model.