The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMM
by Guangquan Zhou; Zhiyu Fu; Yong Liu; Zhengya He; Mengya Cai; Liang Luo
International Journal of Energy Technology and Policy (IJETP), Vol. 19, No. 1/2, 2024

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.

Online publication date: Fri, 10-May-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Energy Technology and Policy (IJETP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com