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The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMM

Author

Listed:
  • Guangquan Zhou
  • Zhiyu Fu
  • Yong Liu
  • Zhengya He
  • Mengya Cai
  • Liang Luo

Abstract

Aiming at the uncertainty of the internal correlation between economic growth, energy consumption and carbon emissions in regional construction industry, a dynamic impact research method based on hidden Markov model (HMM) was proposed. Firstly, the dynamic correlation of three variables in the region was established based on HMM, the optimisation parameter estimation of time window was set, and the optimal prediction of carbon emission state was achieved with Viterbi algorithm. Then, the dynamic parameters of the model with the best prediction effect were obtained, and further describes the evolution of the interaction of the three variables in the region. Finally, the empirical analysis of the East China region shows that the average prediction accuracy of HMM under the optimal time window is more than 93%, and its dynamic parameters intuitively describe the change in regional carbon emission development state and the dynamic relationship between carbon emissions, economic growth, and energy consumption.

Suggested Citation

  • Guangquan Zhou & Zhiyu Fu & Yong Liu & Zhengya He & Mengya Cai & Liang Luo, 2024. "The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMM," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 19(1/2), pages 17-34.
    • Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:17-34
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