IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i24p16582-d999258.html
   My bibliography  Save this article

Variance Analysis in China’s Coal Mine Accident Studies Based on Data Mining

Author

Listed:
  • Tianmo Zhou

    (Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Information Institute of the Ministry of Emergency Management of PRC (IIEM), China Coal Information Institute (CCII), Beijing 100029, China)

  • Yunqiang Zhu

    (Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China)

  • Kai Sun

    (Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China)

  • Jialin Chen

    (Information Institute of the Ministry of Emergency Management of PRC (IIEM), China Coal Information Institute (CCII), Beijing 100029, China)

  • Shu Wang

    (Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China)

  • Huazhong Zhu

    (Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China)

  • Xiaoshuang Wang

    (Beijing Municipal Ecology Environment Bureau Integrating Business Center, Beijing 100048, China)

Abstract

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.

Suggested Citation

  • Tianmo Zhou & Yunqiang Zhu & Kai Sun & Jialin Chen & Shu Wang & Huazhong Zhu & Xiaoshuang Wang, 2022. "Variance Analysis in China’s Coal Mine Accident Studies Based on Data Mining," IJERPH, MDPI, vol. 19(24), pages 1-27, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16582-:d:999258
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/24/16582/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/24/16582/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Hong & Feng, Qun & Zhu, Dandan & Han, Shuai & Long, Ruyin, 2016. "Impact of rent-seeking on productivity in Chinese coal mine safety supervision: A simulation study," Energy Policy, Elsevier, vol. 93(C), pages 315-329.
    2. Jiangshi Zhang & Na Chen & Gui Fu & Mingwei Yan & Young-Chan Kim, 2016. "The Safety Attitudes of Senior Managers in the Chinese Coal Industry," IJERPH, MDPI, vol. 13(11), pages 1-11, November.
    3. Haitao Sun & Jie Cao & Minghui Li & Xusheng Zhao & Linchao Dai & Dongling Sun & Bo Wang & Boning Zhai, 2018. "Experimental Research on the Impactive Dynamic Effect of Gas-Pulverized Coal of Coal and Gas Outburst," Energies, MDPI, vol. 11(4), pages 1-15, March.
    4. Chen, Sen-Sen & Xu, Jin-Hua & Fan, Ying, 2015. "Evaluating the effect of coal mine safety supervision system policy in China's coal mining industry: A two-phase analysis," Resources Policy, Elsevier, vol. 46(P2), pages 12-21.
    5. Yuanlong Li & Xiang Wu & Xiaowei Luo & Jingqi Gao & Wenwen Yin, 2019. "Impact of Safety Attitude on the Safety Behavior of Coal Miners in China," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Lu & Zhao, Qiuhong & Bi, Yanlin, 2020. "Why rent-seeking behavior may exist in Chinese mining safety production inspection system and how to alleviate it: A tripartite game analysis," Resources Policy, Elsevier, vol. 69(C).
    2. Liu, Quanlong & Wang, Jingzhi & Qiu, Zunxiang, 2023. "Data as evidence: Research on the influencing factors and mechanisms of coal mine safety supervision effect in China," Resources Policy, Elsevier, vol. 81(C).
    3. Wang, Yuxin & Fu, Gui & Lyu, Qian & Wu, Yali & Jia, Qinsong & Yang, Xiaoyu & Li, Xiao, 2022. "Reform and development of coal mine safety in China: An analysis from government supervision, technical equipment, and miner education," Resources Policy, Elsevier, vol. 77(C).
    4. Lixia Niu & Rui Zhao, 2022. "The Effect of Safety Attitudes on Coal Miners’ Human Errors: A Moderated Mediation Model," Sustainability, MDPI, vol. 14(16), pages 1-14, August.
    5. Jingzhi, Wang & Quanlong, Liu & Jianping, Shang & Weichao, Niu, 2024. "Research on the impacting mechanism and enhancement strategies for the effect of safety regulation in Chinese coal mine," Resources Policy, Elsevier, vol. 91(C).
    6. Li, Wanzhen & Zhou, Lujie & Hao, Jian & Yu, Kai & Chen, Jing & Liu, Pingping & Feng, Rui, 2023. "Dynamic simulation and control strategy exploration of the unsafe behavior of coal mine employees," Resources Policy, Elsevier, vol. 86(PA).
    7. Yuanlong Li & Jingqi Gao & Chongyang Qian & Xiang Wu, 2022. "The Mediation Role of Safety Attitude in the Impact of Resilience on the Safety Behavior of Coal Miners in China," IJERPH, MDPI, vol. 19(22), pages 1-23, November.
    8. Li, Shuang & Yang, Qifeng & Zhang, Yuhang & Liu, Jiao, 2022. "Multi-agent evolutionary game analysis of the coal mine on-site regulatory mode," Resources Policy, Elsevier, vol. 77(C).
    9. Inmaculada Silla & Francisco J. Gracia & José M. Peiró, 2020. "Upward Voice: Participative Decision Making, Trust in Leadership and Safety Climate Matter," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    10. Yongkang Yang & Qiaoyi Du & Chenlong Wang & Yu Bai, 2020. "Research on the Method of Methane Emission Prediction Using Improved Grey Radial Basis Function Neural Network Model," Energies, MDPI, vol. 13(22), pages 1-15, November.
    11. Shitao Gong & Xin Gao & Zhou Li & Linyan Chen, 2021. "Developing a Dynamic Supervision Mechanism to Improve Construction Safety Investment Supervision Efficiency in China: Theoretical Simulation of Evolutionary Game Process," IJERPH, MDPI, vol. 18(7), pages 1-29, March.
    12. Tan, Jing & Liu, Tianyi & Xu, Hao, 2024. "The environmental and economic consequences of environmental centralization: Evidence from China's environmental vertical management reform," China Economic Review, Elsevier, vol. 84(C).
    13. Jiaqi Li & Yi Tian, 2024. "Assessment of Ecological Quality and Analysis of Influencing Factors in Coal-Bearing Hilly Areas of Northern China: An Exploration of Human Mining and Natural Topography," Land, MDPI, vol. 13(7), pages 1-23, July.
    14. Dzonzi-Undi, Junice & Li, Shixiang, 2016. "Safety and environmental inputs investment effect analysis: Empirical study of selected coal mining firms in China," Resources Policy, Elsevier, vol. 47(C), pages 178-186.
    15. Livhuwani Muthelo & Tebogo Maria Mothiba & Nancy Rambelani Malema & Masenyani Oupa Mbombi & Peter Modupi Mphekgwana, 2022. "Exploring Occupational Health and Safety Standards Compliance in the South African Mining Industry, Limpopo Province, Using Principal Component Analysis," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
    16. Xun Liu & Xiaobo Li, 2022. "Exploring the Formation Mechanism of Unsafe Construction Behavior and Testing Efficient Occupational Health and Safety (OHS) Programs," IJERPH, MDPI, vol. 19(4), pages 1-19, February.
    17. Ismail, Siti Noraishah & Ramli, Azizan & Aziz, Hanida Abdul, 2021. "Influencing factors on safety culture in mining industry: A systematic literature review approach," Resources Policy, Elsevier, vol. 74(C).
    18. Yongliang Deng & Liangliang Song & Zhipeng Zhou & Ping Liu, 2017. "An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network," Complexity, Hindawi, vol. 2017, pages 1-17, October.
    19. Qiao, Wanguan & Liu, Quanlong & Li, Xinchun & Luo, Xixi & Wan, YuLong, 2018. "Using data mining techniques to analyze the influencing factor of unsafe behaviors in Chinese underground coal mines," Resources Policy, Elsevier, vol. 59(C), pages 210-216.
    20. Wu, Bing & Wang, Jingxin & Qu, Baolin & Qi, Pengyuan & Meng, Yu, 2023. "Development, effectiveness, and deficiency of China's Coal Mine Safety Supervision System," Resources Policy, Elsevier, vol. 82(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16582-:d:999258. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.