Research on regional carbon emission prediction method based on combination prediction model

Peng Yuan; Shengnan Liu; Feng Li; Chen Tan; Yinya Zhang; Shouqin Wang

doi:10.1117/12.2684542

19 October 2023 Research on regional carbon emission prediction method based on combination prediction model

Peng Yuan, Shengnan Liu, Feng Li, Chen Tan, Yinya Zhang, Shouqin Wang

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127096H (2023) https://doi.org/10.1117/12.2684542
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Focusing on the coupling relationship between industrial economy, energy power and carbon emissions, this paper combined the decomposition model, autoregressive model and nonlinear regression model of driving factors of carbon emissions to predict regional carbon emissions. The results show that the fitting effect of the combined model is significantly better than that of the single model, which can provide more accurate prediction for the regional carbon peak, and lay a solid foundation for the auxiliary promotion of regional carbon reduction.

Citation Download Citation

Peng Yuan, Shengnan Liu, Feng Li, Chen Tan, Yinya Zhang, and Shouqin Wang "Research on regional carbon emission prediction method based on combination prediction model", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127096H (19 October 2023); https://doi.org/10.1117/12.2684542

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