Forecasting the amount of domestic waste clearance in Shenzhen with an optimized grey model

Abstract

As a leading economic center in China and an international metropolis, Shenzhen has great significance in promoting sustainable urban development. To predict its amount of domestic waste clearance, a new multivariable grey prediction model with combinatorial optimization of parameters is established in this paper. Firstly, the new model expands the value range of the order r of a grey accumulation generation operator from positive real numbers (R +) to all real numbers (R), which enlarges the optimization space of parameter and has positive significance for improving model performance. Secondly, the dynamic background-value coefficient λ is introduced into the new model to improve the smoothing effect of the nearest neighbor generated sequences. Thirdly, with the objective function of minimizing the mean absolute percentage error (MAPE), the particle swarm optimization (PSO) is employed to optimize parameters r and λ to improve the overall performance of the new model. The new model is used to simulate and predict the amount of domestic waste clearance in Shenzhen, and the MAPE of the new model is only 0.27%, which is far superior to several other similar models. Lastly, the new model is applied to predict the amount of domestic waste clearance in Shenzhen. The results indicate the amount of domestic waste clearance in 2028 could be 9.96 million tons, an increase of 20.58% compared to 2021.This highlights the significant challenge that Shenzhen faces in terms of urban domestic waste treatment. Therefore, some targeted countermeasures and suggestions have been proposed to ensure the sustainable development of Shenzhen's economy and society.