An improved multi-variable grey model for forecasting China's finished products from comprehensive waste utilization

Abstract

A reasonable prediction of the finished products from waste recycling and reprocessing is of great significance to the sustainable use of limited resources, the reduced pollution caused by waste, and the reflected comprehensive waste utilization (CWU) creativity. To this end, an improved multi-variable grey model was employed to forecast the finished products in China's CWU. Firstly, the degree of grey incidence was applied to select explanatory variables and eliminate multicollinearity between them. Then, compared with the traditional GM(1,N) model, the linear correction term and grey action quantity were added in the proposed improved model, and the response function and parameter estimation method of the improved model were deduced and proved. Thirdly, the finished products from CWU was simulated and predicted by the proposed model. The mean relative simulation percentage error of the improved model was only 0.0001%, in comparison with the ones obtained from the traditional GM(1,N) and the classical GM(1,1), which were 12.1232 and 8.8402%, respectively. Lastly, the results show that the finished products from CWU are mainly affected by the comprehensive utilization of general industrial solid waste and the number of industrial enterprises in CWU, and the future trends from 2020 to 2025 are unstable.

Keywords: Comprehensive waste utilization; Comprehensive waste utilization creativity; Grey incidence analysis; Multi-variable grey prediction model; Prediction of finished products.