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《Control Engineering of China》 2008-S1
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Water Demand Forecast Based on ARIMA Time-series Identification

LIAN Ting-hong,LIU Qiu-juan,WANG Jing-cheng(Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China)  
Water supply industry is a significant basis of national economy.It's helpful for the water supply administration to make decisions by forecasting water demand.To the city water demand fluctuation character and forecast requirement,ARIMA seasonal time-series model is applied for forecasting.Time-series model order is identified by analyzing parameters such as ACF,PACF.Future water demand trend is forecast and SAS statistical software is applied to verify the result.The ARIMA model proposed has been successfully applied to the Shanghai water supply forecast project.Contrast with historical data,it can provide ideal precision to the forecast,and help water supply administration to make decisions reliably.
【Fund】: 上海启明星计划基金资助项目(07QA14030)
【CateGory Index】: TU991.31;TN911.72
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