Research and Application of Urban Water Demand Forecasting
 Based on Time Difference Coefficient

doi:10.16183/j.cnki.jsjtu.2017.10.016

Abstract

Abstract: The support of water supply system has been a concerned focus of urban construction. The accurate prediction of short term water quantity is important for the whole water system operation and maintenance. In this paper, the intelligent scheduling management system for raw water based on least square support vector machine with improved particle swarm optimization is proposed by means of the project Shanghai Qingcaosha Intelligent Raw Water Dispatch and Management System. After analyzing the characteristics of water quantity data, the results of water quantity prediction have a big deviation from the actual water supply during the holidays. So forecasting model of daily and hourly water demand is built based on time difference coefficient to optimize the original prediction model. Combined with the actual operation and process conditions of water plant, this optimized model is applied to water plant to provide more accurate water supply scheduling suggestion.

Key words: water demand forecasting, time difference coefficient, particle swarm optimization algorithm, least square support vector machine

CLC Number:

TP 29

LUO Huayi,WANG Jingcheng,YANG Liwen,LI Xiaocheng. Research and Application of Urban Water Demand Forecasting
Based on Time Difference Coefficient[J]. Journal of Shanghai Jiaotong University, 2017, 51(10): 1260-1267.

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