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Prediction of Carbon Emissions Level in China’s Logistics Industry Based on the PSO-SVR Model

Author

Listed:
  • Liang Chen

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

  • Yitong Pan

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

  • Dongqing Zhang

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

Abstract

Adjusting the energy structure of various industries is crucial for achieving China’s carbon peak and carbon neutrality goals. Given the significant proportion of carbon emissions from the logistics industry in the tertiary sector, the research on predicting the carbon emissions of the logistics industry is of great significance for China to achieve its “Dual carbon” target. In this paper, the gray relational analysis (GRA) methodology is adopted to screen the influencing factors of carbon emissions in the logistics industry firstly. Then, the particle swarm optimization (PSO) algorithm was used to optimize the penalty coefficientand kernel function range parameter of the support vector regression (SVR) model (i.e. PSO- SVR model). The data from 2000 to 2021 regarding carbon emissions and related influencing factors in China’s logistics industry are analyzed, and the mean absolute percentage error (MAPE) of the PSO-SVR model is 0.82%, which shows that the proposed PSO-SVR model in this paper is effective. Finally, instructive suggestions are provided for China to achieve the “Dual Carbon” goal and upgrading of the logistics industry.

Suggested Citation

  • Liang Chen & Yitong Pan & Dongqing Zhang, 2024. "Prediction of Carbon Emissions Level in China’s Logistics Industry Based on the PSO-SVR Model," Mathematics, MDPI, vol. 12(13), pages 1-13, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:1980-:d:1422964
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    References listed on IDEAS

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    1. Shuai Zhao & Zhou Zhao, 2021. "A Comparative Study of Landslide Susceptibility Mapping Using SVM and PSO-SVM Models Based on Grid and Slope Units," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-15, January.
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