Prediction model of agricultural non-point source water pollution based on grey correlation method

Abstract

Accurate prediction of non-point source water pollution is conducive to the prevention and control of rural water pollution. To improve the prediction accuracy of agricultural non-point source water pollution and achieve timely prevention and control, a prediction model of agricultural non-point source water pollution based on the grey correlation method is designed. According to the historical data of agricultural nonpoint source water pollution, the influencing factors of water pollution degree are determined by using the grey correlation method, and standardized pretreatment is carried out. The pretreatment results are transformed into function expression forms, and the original sequences of different influencing factors are generated, which are brought into the function table to achieve the results, and the whitening differential equation is constructed to measure the concentration of agricultural non-point source water pollution. The structure design of the prediction model of agricultural non-point source water pollution can realize the prediction of agricultural non-point source water pollution. The results show that the prediction model of agricultural non-point source water pollution based on the grey correlation method has high prediction accuracy and small prediction error.