中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining

文献类型:期刊论文

作者Zhou, Tianmo2,3,4; Zhu, Yunqiang1,2; Sun, Kai2; Chen, Jialin4; Wang, Shu2; Zhu, Huazhong2; Wang, Xiaoshuang5
刊名INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
出版日期2022-12-01
卷号19期号:24页码:27
关键词China coal mine accidents Apriori LSI variance analysis data mining CiteSpace
DOI10.3390/ijerph192416582
通讯作者Zhu, Yunqiang(zhuyq@lreis.ac.cn) ; Sun, Kai(sunk@lreis.ac.cn)
英文摘要The risk of coal mine accidents rises significantly with mining depth, making it urgent for accident prevention to be supported by both scientific analysis and advanced technologies. Hence, a comprehensive grasp of the research progress and differences in hotspots of coal mine accidents in China serves as a guide to find the shortcomings of studies in the field, promote the effectiveness of coal mine disaster management, and enhance the prevention and control ability of coal mine accidents. This paper analyzes Chinese and foreign literature based on data mining algorithms (LSI + Apriori), and the findings indicate that: (1) 99% of the available achievements are published in Chinese or English-language journals, with the research history conforming to the stage of Chinese coal industry development, which is characterized by "statistical description, risk evaluation, mechanism research, and intelligent reasoning". (2) Chinese authors are the primary contributors that lead and contribute to the continued development of coal mine accident research in China globally. Over 81% of the authors and over 60% of the new authors annually are from China. (3) The emphasis of the Chinese and English studies is different. Specifically, the Chinese studies focus on the analysis of accident patterns and causes at the macroscale, while the English studies concentrate on the occupational injuries of miners at the small-scale and the mechanism of typical coal mine disasters (gas and coal spontaneous combustion). (4) The research process in Chinese is generally later than that in English due to the joint influence of the target audience, industrial policy, and scientific research evaluation system. After 2018, the Chinese studies focus significantly on AI technology in deep mining regarding accident rules, regional variation analysis, risk monitoring and early warning, as well as knowledge intelligence services, while the hotspots of English studies remain unchanged. Furthermore, both Chinese and English studies around 2019 focus on "public opinion", with Chinese ones focusing on serving the government to guide the correct direction of public opinion while English studies focus on critical research of news authenticity and China's safety strategy.
WOS关键词SAFETY SUPERVISION ; RISK-ASSESSMENT ; GAS EXPLOSION ; MANAGEMENT ; AHP
资助项目Internet Security and Informatization of CAS ; Strategic Priority Research Program of the Chinese Academy of Sciences ; [CAS-WX2021SF-0106] ; [XDA23100100]
WOS研究方向Environmental Sciences & Ecology ; Public, Environmental & Occupational Health
语种英语
出版者MDPI
WOS记录号WOS:000900909900001
资助机构Internet Security and Informatization of CAS ; Strategic Priority Research Program of the Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/188314]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, Yunqiang; Sun, Kai
作者单位1.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China
2.Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.China Coal Informat Inst CCII, Informat Inst Minist Emergency Management PRC IIEM, Beijing 100029, Peoples R China
5.Beijing Municipal Ecol Environm Bur, Integrating Business Ctr, Beijing 100048, Peoples R China
推荐引用方式
GB/T 7714
Zhou, Tianmo,Zhu, Yunqiang,Sun, Kai,et al. Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining[J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,2022,19(24):27.
APA Zhou, Tianmo.,Zhu, Yunqiang.,Sun, Kai.,Chen, Jialin.,Wang, Shu.,...&Wang, Xiaoshuang.(2022).Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,19(24),27.
MLA Zhou, Tianmo,et al."Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 19.24(2022):27.

入库方式: OAI收割

来源:地理科学与资源研究所

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