Long-Term Prediction of Domestic Water Demand Using Bayesian Belief Networks
According to the water scarcity in recent decades in Iran, long-term prediction of domestic water consumption is a beneficial approach in order to manage water demand and water supply in water distribution systems. Therefore, it is necessary to develop a model which is capable of demonstrating the complexity, uncertainties, and influences of various parameters on water consumption with high accuracy. The increment of uncertainties in the forecasting period leads to apply probability methods such as Bayesian belief networks in addition to deterministic methods. This paper presents two Bayesian networks to predict long-term water demand in Neyshabour city. Furthermore, the efficiency of those models is compared to the Stone-Geary function; moreover, their sensitivity to the network structure and data categories is evaluated.
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Selection of the Best Statistical Index of Nodal Pressure Values for Use in Calibrating the Hydraulic Model of the Water Distribution Network Based on Field Data Processing
Mehdi Dini *, Roghayeh Mashhadi Alizadeh, , Saeed Hashemi
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Abbas Abbasi *, Keivan Khalili, Javad Behmanesh,
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