基于BP神经网络构建城市时需水量预测模型  

An BP ANN Forecast Model for Hourly Water Demand of Urban Water-distribution System

作　　者：金建华[1] 史义雄[1] 史永刚[2] 

机构地区：[1]武汉理工大学土木工程与建筑学院,湖北武汉430070 [2]电子科技大学计算机科学与工程学院,四川成都610054

出　　处：《城市管理与科技》2005年第1期29-31,共3页Urban Management and Science & Technology

摘　　要：　　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.

关 键 词：需水量预测 水厂 结合水 基础 供水系统 城市 计算程序 天气因素 模型 构建 

分 类 号：F224[经济管理—国民经济]