Dezhi Zheng

Prof. Dr. Dezhi Zheng


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 May 2022 in Geofluids
Verified
Journal Article
Open access
PDF file
JBJinyan Bai
Jinyan Bai
DZDezhi Zheng
Dezhi Zheng
CJChen Jia
Chen Jia
At present, China’s intelligent coal mine construction is still in the primary development stage. The integrated development of a new generation of information and communication technology and the coal industry is accelerating, and this industry’s intelligent green transformation and upgrading is being promoted. With the continuous acceleration of China’s intelligent coal mine construction and the continuous improvement in the degree of coal mine intelligence, system compatibility, information acquisition, and intelligent research have raised awareness of new mining safety risks. Based on the analysis of the process of China’s intelligent construction, this paper describes the safety management and control risks and the technical challenges faced by China’s intelligent coal mine construction in terms of norms and standards, data acquisition, subsystem and terminal sensors, multisystem integration, safety risk management, and control ability. It is important to make full use of the collaborative advantages of intelligent scientific and technological coal mine resources. Technological innovation and intelligent equipment safety access verification need to be supported, so as to promote the intelligent and high-quality development of coal mines.

8 June 2022 in Geofluids
Verified
Journal Article
Open access
PDF file
XGXuyang Guo
Xuyang Guo
XWXin Wang
Xin Wang
DZDezhi Zheng
Dezhi Zheng
This paper attempts to study the effect of China’s coal consumption on the upgrading of industrial structure based on the relevant data obtained from the China Statistical Yearbook (1992–2021). The results showed that (1) China’s coal consumption has a downward trend, but it is still more than 56.8%. Similarly, the consumption of nonpetrochemical energy is not high, but the increase with respect to time is large. (2) Percentage of China’s tertiary industry reached a maximum of 54.5% in 2020. However, there is a huge gap when compared to the global data. For example, the tertiary industries accounted for 77.4% in the US in 2017 and 71.3% in the UK in 2019. (3) In the short term, China’s coal consumption will continue to promote the upgrading of industrial structure; in the long run, it is not obvious that China’s coal consumption continues to drive the upgrading of industrial structure. (4) The intensity of the sustainable driving effect of China’s coal consumption on the upgrading of industrial structure will gradually weaken from 0.0647 to 0.00102.

27 March 2025 in Energies
Verified
Journal Article
Open access
PDF file
SRShihua Ren
Shihua Ren
XJXiaomiao Jiao
Xiaomiao Jiao
DZDezhi Zheng
Dezhi Zheng
YZYaning Zhang
Yaning Zhang
HXHeping Xie
Heping Xie
RZRui Zhang
Rui Zhang
China’s coal industry is reckoned as one of the topmost contributors to global carbon emissions, and as a result, poses severe challenges both to human health and climate change mitigation efforts. Achieving carbon neutrality requires thorough analyses of mechanisms driving the coal sector’s transition. This study employs a structural model to investigate the transmission pathways through/by which the “dual carbon” goals influence the coal industry, using a policy text quantification approach to assess specific carbon reduction measures. Findings reveal that the impact of the “dual carbon” target on the coal industry operates through multiple pathways. Carbon reduction policies significantly enhance technical advancements, social and economic factors, energy-saving measures, and alternative energy development, all of which indirectly affect coal supply. Notably, the pathway from coal demand to coal supply shows a high path coefficient of 1.121, far surpassing the path coefficient from factor input to coal supply, measured at 0.169. This highlights coal demand as the pivotal intermediary variable in determining the “dual carbon” target’s impact on the coal industry. While current technologies and alternative energy sources have limited immediate effects on coal supply, they hold significant potential as transformative factors in the future.

1 January 2021 in Advances in Civil Engineering
Verified
Journal Article
Open access
PDF file
SRShihua Ren
Shihua Ren
DZDezhi Zheng
Dezhi Zheng
YQYang Qu
Yang Qu
RQRongjun Qin
Rongjun Qin
MJMiao Xiao Jiao
Miao Xiao Jiao
JBJinyan Bai
Jinyan Bai
Coal is the most reliable energy resource in China and has been in existence for a long time. The development model of coal industry is of great significance to carbon emission and environmental protection. In order to evaluate the development mode of China’s coal industry, this paper presents the constructed evaluation index system of the development mode of the coal industry from two dimensions, demand pull and factor drive. And, coal consumption is the measurement index of demand pull and selecting resources, capital, technology, human resources, and the energy system form the measurement index of factor drive. By analyzing the evaluation index system of the coal industry development mode and optimal evaluation method, the minimum deviation comprehensive weighting evaluation model, based on the analytic hierarchy process (AHP), and entropy are constructed. The evaluation results show that the coal industry has continued the factor driven growth, driven by demand, in the past decades. Finally, the study analyzes the changes and challenges of the development of China’s coal industry from four aspects, development power, development mode, development effect, and development bottleneck, to provide support for revealing the internal mechanism of the development mode of China’s coal industry.

4 May 2023 in Discrete Dynamics in Nature and Society
Verified
Journal Article
Open access
PDF file
GZGuodang Zhao
Guodang Zhao
XGXuyang Guo
Xuyang Guo
XWXin Wang
Xin Wang
DZDezhi Zheng
Dezhi Zheng
Currently, coal is still the main energy source for China’s economic development, and the environmental issues caused by coal consumption have aroused widespread concern. Predicting and analyzing coal consumption will help to formulate a higher level of energy consumption planning and economic development strategy. The main purpose of this study is to develop a new fractal time-series prediction (FTSP) model to predict coal consumption, providing reference for formulating effective energy consumption planning and economic development strategies. Hurst index is an important indicator of whether time-series data have long memory and fractal characteristics. This paper uses the rescaled range (R/S) method to calculate Hurst index of the coal consumption per-10000-Yuan-GDP (CC/GDP). The Hurst index is 0.8025, exceeding 0.5, indicating that the time-series data CC/GDP has a long memory and fractal characteristic. Based on this, this paper uses the FTSP model to predict China’s coal consumption (CC/GDP). The prediction results show that the FTSP model accurately predicted China’s coal consumption with a relative error rate (RER) of less than 5% and a mean absolute percentage error (MAPE) of 6.62%. The model predicts a decrease in China’s coal consumption from 0.25 tons of standard coal in 2021 to 0.11 tons of standard coal in 2030, a decrease of 44%. To sum up, the FTSP model provides a new and accurate way to predict coal consumption, and the results suggest that China’s coal consumption is sustainable and will decrease significantly in the coming years. This study has important implications for energy consumption planning and economic development strategies.

29 July 2023 in Complexity
Verified
Journal Article
Open access
PDF file
GZGuodang Zhao
Guodang Zhao
XGXuyang Guo
Xuyang Guo
XWXin Wang
Xin Wang
DZDezhi Zheng
Dezhi Zheng
The study of coal consumption has become a focus of academic attention due to ecological and environmental concerns. This study proposed a method to evaluate sustainability for coal consumption by using a multiple-attribute decision-making (MADM) model. The data used are from the China Statistical Yearbook and the China Energy Statistical Yearbook over the years. The MADM model consists of attributes (standards), their importance weights, and alternatives. The comprehensive evaluation system for the sustainability of coal consumption, which was composed of four first-grade indicators including coal strength (CS), energy dependency (ED), social development level (SL), and population size (PS) and their corresponding 20 second-grade indicators, was included in the MADM model as attributes (standards). The importance weight of the attributes was determined by the entropy weight method (EWM) and the analytic hierarchy process (AHP), while the comprehensive evaluation of the sustainability of coal consumption in China over the years was considered as an alternative. The evaluation indices of four first-grade indicators were obtained through multiobjective optimization, and then through the weights and evaluation indices of the four first-grade indicators, multiobjective optimization was carried out for the overall objective of the comprehensive evaluation of the sustainability of coal consumption over the years, and the comprehensive evaluation indices of the sustainable development of coal consumption over the years were obtained. The results show that China’s coal consumption is sustainable, with the composite assessment index rising from 0.058 in 2011 to 0.837 in 2021, an increase of 13.4 times.