 The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMMGuangquan Zhou, Zhiyu Fu, Yong Liu, Zhengya He, Mengya Cai and Liang Luo International Journal of Energy Technology and Policy, 2024, vol. 19, issue 1/2, 17-34 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. Keywords: building carbon emissions; improved HMM; state prediction; dynamic impact. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:17-34 Access Statistics for this article More articles in International Journal of Energy Technology and Policy from Inderscience Enterprises Ltd |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.