Knowledge map analysis of coal mine water disaster prevention and control in China from 2000 to 2023

被引:2
|
作者
Lu, Cunjin [1 ]
Li, Pu [1 ]
Xu, Jinpeng [1 ]
Chai, Jincheng [1 ]
机构
[1] China Univ Min & Technol, Sch Resources & Geosci, Xuzhou 221116, Peoples R China
关键词
CiteSpace; China coal mine; Water disaster prevention; Knowledge graph; Visualized analysis;
D O I
10.1007/s12145-024-01353-z
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
To understand the development status and frontier trends in the prevention and control of coal mine water hazards, a dataset of 962 articles indexed in Web of Science was used. Visualization maps were created using CiteSpace software to conduct statistical analyses on the publication volume, journal distribution, researchers, research institutions, keywords, and burst terms in the field of coal mine water hazard prevention and control in China from 2000 to 2023. The study reveals that the number of publications related to the prevention and control of coal mine water hazards in China has gone through rapid growth periods as well as stable fluctuations. The literature cooperation network in the field of coal mine water hazard prevention and control consists of two main collaboration groups and a series of independent authors, with the core research strength concentrated in institutions such as China University of Mining and Technology, Shandong University of Science and Technology, China University of Mining and Technology (Beijing), and Xi'an Research Institute of China Coal Technology and Engineering Group. Keywords such as "Coal mine water hazards," "Water inrush," "numerical simulation," "aquifer," and "risk assessment" collectively form larger clusters, primarily revolving around three main research directions: "water source," "water inflow pathways," and "water inflow intensity." In-depth exploration of the mechanisms of water inrush in coal mines, the revelation of water-conducting fracture evolution patterns, understanding underground water seepage characteristics, and hydraulic characteristics, along with the extensive use of new technologies like artificial intelligence and big data, will be the future hotspots in research.
引用
收藏
页码:2791 / 2799
页数:9
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