Research on Urban Water Demand Prediction

Abstract

Water demand prediction adopts combined prediction method based on BP neural network prediction model, grey G (1,1) prediction model, time sequence prediction model (second multinomial exponential smoothing model) and single linear regression model (Cubics Ratio model). Empirical results show that combined prediction method makes comprehensive use of information of every separate prediction model, and thus enhances prediction accuracy.