College of Business Administration, Chongqing Technology and Business University, Chongqing, 400067, People's Republic of China.
College of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, People's Republic of China.
Environ Sci Pollut Res Int. 2021 Aug;28(31):42901-42915. doi: 10.1007/s11356-021-13737-5. Epub 2021 Apr 7.
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.
对废料回收和再加工的成品进行合理预测，对于有限资源的可持续利用、减少废料造成的污染以及体现全面的废料综合利用（CWU）创意都具有重要意义。为此，采用改进的多变量灰色模型对中国 CWU 的成品进行预测。首先，应用灰色关联度分析选择解释变量，并消除它们之间的多重共线性。然后，与传统的 GM(1,N)模型相比，在提出的改进模型中增加了线性修正项和灰色作用量，并推导出和证明了改进模型的响应函数和参数估计方法。接着，用提出的模型对 CWU 的成品进行模拟和预测。改进模型的平均相对模拟百分比误差仅为 0.0001%，而传统的 GM(1,N)和经典 GM(1,1)模型的误差分别为 12.1232%和 8.8402%。最后，结果表明，CWU 的成品主要受到一般工业固体废物综合利用和 CWU 中工业企业数量的影响，2020 年至 2025 年的未来趋势不稳定。
