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

Authors: Guangquan Zhou; Zhiyu Fu; Yong Liu; Zhengya He; Mengya Cai; Liang Luo

Addresses: Anhui Province Key Laboratory of Green Building and Assembly Construction, Anhui Institute of Building Research and Design, Heifei, Anhui, 230031, China; School of Civil Engineering, Nanchang Hangkong University, Nanchang, 330063, China ' School of Civil Engineering, Nanchang Hangkong University, Nanchang, 330063, China ' Beijing Public Highway Link Co., Ltd., Beinjing, 100161, China ' Anhui Province Key Laboratory of Green Building and Assembly Construction, Anhui Institute of Building Research and Design, Heifei, Anhui, 230031, China ' Anhui Province Key Laboratory of Green Building and Assembly Construction, Anhui Institute of Building Research and Design, Heifei, Anhui, 230031, China ' School of Civil Engineering, Nanchang Hangkong University, Nanchang, 330063, China

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.

DOI: 10.1504/IJETP.2024.138536

International Journal of Energy Technology and Policy, 2024 Vol.19 No.1/2, pp.17 - 34

Received: 23 May 2023
Accepted: 19 Oct 2023
Published online: 10 May 2024 *

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