Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions

Pingping Xiong (), Xiaojie Wu and Jing Ye
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Pingping Xiong: Nanjing University of Information Science and Technology
Xiaojie Wu: Nanjing University of Information Science and Technology
Jing Ye: Nanjing University of Finance & Economics

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 9, No 28, 9647-9671

Abstract: Abstract With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance.

Keywords: Grey system theory; Multivariate prediction model; Parameter optimization; Industrial sector (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02453-w

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