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中国管理科学 ›› 2022, Vol. 30 ›› Issue (4): 96-107.doi: 10.16381/j.cnki.issn1003-207x.2020.0657

• 论文 • 上一篇    下一篇

基于灰色参数组合优化新模型的生活垃圾清运量预测研究

李惠,曾波,周文浩   

  1. 重庆工商大学管理科学与工程学院,重庆400067
  • 收稿日期:2020-04-13 修回日期:2020-09-02 出版日期:2022-04-20 发布日期:2022-04-26
  • 通讯作者: 曾波(1975-), 男(汉族), 四川内江人, 重庆工商大学管理科学与工程学院,教授,博士,研究方向:不确定性系统预测决策建模方法及其应用,Email:bozeng@ctbu.edu.cn. E-mail:bozeng@ctbu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(72071023,71771033);重庆市基础研究与前沿探索专项项目(cstc2019jcyj-msxmX0003,cstc2019jcyj-msxmX0767);重庆市教委科学技术研究重点项目(KJZD-K202000804);重庆市研究生科研项目(CYS21390)

Forecasting Domestic Waste Clearing and Transporting Volume by Employing A New Grey Parameter Combination Optimization Model

LI Hui, ZENG Bo, ZHOU Wen-hao   

  1. School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing 400067, China
  • Received:2020-04-13 Revised:2020-09-02 Online:2022-04-20 Published:2022-04-26
  • Contact: 曾波 E-mail:bozeng@ctbu.edu.cn

摘要: 准确的生活垃圾清运量预测是环保部门制定生活垃圾处置政策措施的重要依据。为此,文章首先在新结构多变量灰色预测模型基础上,对自变量驱动项、累加阶数、背景值系数进行组合优化,推导并构建了适用于生活垃圾清运量预测的新型多变量灰色系统模型。然后,应用该模型对江苏省垃圾清运量进行实例分析,结果显示该模型综合误差仅为0.996%,其性能优于同类其他多变量灰色预测模型(1.933%、4.894%)。最后,应用该模型对江苏省未来清运量进行了预测,并提出了相关的对策和建议。本研究成果为环保部门制订相关政策措施提供了参考依据,同时为生活垃圾清运量预测提供了一种有效的建模方法。

关键词: 生活垃圾清运量;多变量灰色预测模型;参数组合优化;对策建议

Abstract: Accurate prediction of domestic waste clearing and transporting volume is an important basis for environmental protection departments to formulate policies and measures for the disposal of domestic garbage. Firstly, the combination optimization of the independent variable driving term, the accumulation order and the background value coefficient is carried out on the basis of the multi-variable grey forecasting model with new structure, and a novel multi-variable grey system model suitable for prediction of domestic waste clearing and transporting volume is derived and constructed. Secondly, domestic waste clearing and transporting volume in Jiangsu Province is modelled by this new model, the results show that its comprehensive error is only 0.996%, and the accuracy of the model is superior to other multi-variable grey forecasting models (1.933%, 4.894%). Finally, this model is applied to predict domestic waste clearing and transporting volume in Jiangsu Province, the results show that its clearing and transporting volume will maintain an average annual growth rate of about 7% in the next 10 years and reach 32.2159 million tons in 2028. Therefore, the relevant countermeasures and suggestions are put forward. A reference basis is provided for environmental protection departments to formulate relevant policies and measures, and an effective modeling method is also provided for the prediction of domestic waste clearing and transporting volume.

Key words: domestic waste clearing and transporting volume; multi-variable grey forecasting model; parameters’ combination optimization; countermeasure and suggestion

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