Water Pollution Prevention and Prediction Based on Grey BP Neural Network Model

Abstract

With the acceleration of economic development, the problem of water pollution (WP) has also become a problem for many countries around the world. In the process of development, many countries have experienced serious WP phenomena, which have had a very serious impact on the ecological environment. The main reason why people attach importance to the problem of WP is that water is indispensable for the development of society and the survival of human beings, and if serious WP problems occur, people's water safety will not be guaranteed. Based on the grey BP neural network (BPNN) model, this paper predicts the pollution emissions in 2023 for the industrial and livestock pollution emission coefficient of M city from 2016 to 2020. The results show that the combination of grey system theory and BPNN can effectively predict the WP emissions. Through analyzing the WP prevention and control problems in M city, this paper puts forward prevention and control strategies, hoping that this study can also provide reference and suggestions for WP control in other cities.