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Forecasting Chinese Carbon Emissions from Fossil Energy Based on the Fractional Order Cumulative Multivariate Grey Model

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Listed:
  • Yunxin Zhang
  • Huan Guo
  • Xin Xiong

Abstract

In the process of Chinese economic development shifting from a stage of high‐speed growth to a stage of high‐quality development, carbon emissions caused by fossil energy consumption are also increasing. To reflect the interaction between Chinese carbon emissions from fossil energy consumption and economic growth, this paper constructed the fractional order cumulative multivariate gray model with equal‐dimensional recursive optimization (EFMGM(1,2)) to predict the trend of carbon emissions from fossil energy consumption and constant price GDP in China and calculated the carbon emissions from fossil energy consumption according to the IPCC accounting method. EFMGM(1,2) is compared with other gray models to verify the performance of the model. The results show that this model has better prediction performance than other models. It can be used as an effective method for forecasting carbon emissions from fossil energy.

Suggested Citation

  • Yunxin Zhang & Huan Guo & Xin Xiong, 2022. "Forecasting Chinese Carbon Emissions from Fossil Energy Based on the Fractional Order Cumulative Multivariate Grey Model," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:5623519
    DOI: 10.1155/2022/5623519
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