基于BP神经网络构建城市时需水量预测模型
n BP ANN Forecast Model for Hourly Water Demand of Urban Water-distribution System
城市供水系统需水量预测对系统优化调度和提高管理水平具有非常重要的作用。针对建立精确的时需水量与其影响因素的显式预测模型比较困难的问题，在研究天气因素对供水系统日需水量影响的基础上，建立了时需水量天气因素敏感的BP模型。结合水厂的实际供水量历史数据，基于MATLAB语言编写相关计算程序，验证了模型的可行性。
Water demand forecast plays an important role in the control and operation of water-distribution system．Hourly water demand is influenced by many factors，but it is difficult to establish an accurate model on them．Based on the study of effect of weather factors on daily water demand，the forecast method is presented，and BP model of ANN and calculation are set up．The data from water plants are employed to forecast hourly demand，and the error analysis of the result demonstrates the model is effective．
史永刚、金建华、史义雄
自动化技术经济计算技术、计算机技术
时需水量预测人工神经网络BP模型MATLAB
hourly water demandforecastNNBP modelMATLAB
史永刚,金建华,史义雄.基于BP神经网络构建城市时需水量预测模型[EB/OL].(2004-11-26)[2025-08-04].http://www.paper.edu.cn/releasepaper/content/200411-115.点此复制
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