Analysis and Prediction of Water Consumption in Nanjing—A Comparative Study Based on Stepwise Regression and Nonparametric Mode

Abstract

Accurate prediction of urban water consumption is of great significance to the management and improvement of water supply system. In this thesis, through correlation analysis on 16 factors affecting total water consumption in Nanjing from 2005 to 2019, the factors among them that have more obvious influence are selected, and then they are fitted by stepwise linear regression model and nonparametric regression model respectively. By comparing the fitting results, it is found that nonparametric regression model has better prediction effect than stepwise regression model. The analysis results show that the prediction of urban water consumption is very important for the rational allocation of water resources.