MODELING AND FORECASTING OF URBAN WATER SHORT-RUN DEMAND

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SADEGHI HOSSEIN; ZOLFAGHARI MAHDI; ARAM RAHMAN

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Journal: Journal of Economic Studies and Policies Year:2012 | Volume:7 (17) | Issue:2 (87) Page(s): 159-172

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Information Journal Paper

Title

MODELING AND FORECASTING OF URBAN WATER SHORT-RUN DEMAND

Author(s)

SADEGHI HOSSEIN | ZOLFAGHARI MAHDI | ARAM RAHMAN | Issue Writer Certificate

Keywords

DEMAND WATERQ2

FORECASTINGQ2

ARTIFICIAL NEURAL NETWORKSQ2

ARMAQ3

Abstract

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.

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APA: Copy

SADEGHI, HOSSEIN, ZOLFAGHARI, MAHDI, & ARAM, RAHMAN. (2012). MODELING AND FORECASTING OF URBAN WATER SHORT-RUN DEMAND. JOURNAL OF ECONOMIC STUDIES AND POLICIES, 7 (17)(2 (87)), 159-172. SID. https://sid.ir/paper/219087/en

Vancouver: Copy

SADEGHI HOSSEIN, ZOLFAGHARI MAHDI, ARAM RAHMAN. MODELING AND FORECASTING OF URBAN WATER SHORT-RUN DEMAND. JOURNAL OF ECONOMIC STUDIES AND POLICIES[Internet]. 2012;7 (17)(2 (87)):159-172. Available from: https://sid.ir/paper/219087/en

IEEE: Copy

HOSSEIN SADEGHI, MAHDI ZOLFAGHARI, and RAHMAN ARAM, “MODELING AND FORECASTING OF URBAN WATER SHORT-RUN DEMAND,” JOURNAL OF ECONOMIC STUDIES AND POLICIES, vol. 7 (17), no. 2 (87), pp. 159–172, 2012, [Online]. Available: https://sid.ir/paper/219087/en

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