The Forecasting of Water Resource Based on Neural Network

Abstract

With the development of modern industry and the growth of population, water shortage has become a growing concern for the world. In this paper, from the influencing factors of supply and demand, the relationship between supply and demand is established to measure the ability to provide clean water in one region. And to analyze the factors that affect water scarcity specifically, Beijing is selected as the research object. The data show that the over-exploitation of groundwater is the main reason for water shortage in Beijing. Then all kinds of water resource are predicted in the following years by BP Neural Network. However, the result is not consistent with the actuals. So an improved BP neural network is proposed to reforecast, the result of this improved BP Neural Network is closer to the actuals. In addition, gray system theory is also used to predict the monotonous water quantity.