نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Water is one of the most importance sources for provision of the human needs that plays a vital role in current life. Therefore awareness about water demand is important for necessary policy making for demand management. In this paper we modeled Tehran water daily demand by nonlinear Artificial Neural Network and linear process of ARMA for a 7 years period and forecasted the urban water daily demand for 10 days. The effective factors on urban water daily demand in designing of neural network are temperature (minimum, average, maximum), week days, holidays and special days. Results present that artificial neural network have higher power than ARMA in forecasting the Tehran city water daily demand on the basis of indicators of forecast accuracy valuation.
کلیدواژهها English
Bithas Kostas, "Stoforos Chrysostomos, Estimating urban Residential water Demand Determinants and Forecasting Water Demand For Athens Metropolitan Area", 2000-2010, South-Eastern Europe Journal of Economics, Vol. 1, 2006.
Jain, Ashu et al; "Short-term Water demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks", Water Resources Management, 2001, No. 15.
K.B. Khatri; K. Vairavamoorthy; "Water Demand Forecasting for the City of the Future against the Uncertainties and the Global Change Pressures: Case of Birmingham", EWRI/ASCE: 2009, Conference: Kansas, USA May, 2009.
Liu, J; Savenije, H.G & Xu, J;"Forecast of Water Demand in Weinan City in China Using WDF-ANN Model", Physics and Chemistry of the Earth, Vol. 28, 2002.
Maidment, D. R. & Parzen, E; "Cascade model of monthly municipal water use" J. of Water Resources Research, Vol. 20, 1984, No. 1.
Maidment, D. R; Miaou, S. P & Crawford, M. M; "Transfer function models of daily urban water use", J. of Water Resources Research, Vol. 21, 1985, No. 4.
Ravindra Sen Pillay; Short-Term Water Demand Forecasting for Production Optimisation, University of Southern Queensland Faculty of Engineering and Surveying, 2005.
Stark, H.L; Stanley, J.S; Buchanan, I.D; Water Demand Forecasting Using Artificial Neural Networks, University of Alberta, 2000.
Yu, M.J; Joo, C.N; Koo, J.Y; "Application of Short-Term Water Demand Prediction Model to Seoul", Journal of Water Science & Technology, Vol. 46, 2002, No. 6-7.