Industrial Carbon Emission Prediction Model Based on Artificial Intelligence

Author:

Song Chaohan

Publisher

Springer Nature Switzerland

Reference11 articles.

1. Yuan, Q., Zhang, Z., Zhao, X.: Study on dynamic characteristics and flow structure of industrial carbon emissions in China. Ind. Techn. Econom. 42(8), 80–89 (2023)

2. Zhang Ting, X., Shujie, L.J., et al.: Research on carbon emission reduction measures and implementation path of carbon peaking in industrial field. China Manag. Inform. Technol. 25(24), 22–27 (2022)

3. Wanbing, C., Xue-Bin, L.: Carbon emission trading price prediction using ARMI-SSA-LSTM model. J. Xi ‘an Univ. Sci. Technol. 43(5), 1025–1034 (2023)

4. Xinlong, J., Qingrui, Z.: Scenario prediction of industrial carbon emissions peaking based on extended STIRPAT model. J. Lanzhou Univ. Arts Sci. Soc. Sci. Edn. 39(3), 99–107 (2023)

5. Hua-zheng, T., Li, M.: Study on the change of China’s industrial carbon emission intensity from the perspective of sector structure. J. Nat. Resour. 35(3), 639–653 (2020)

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