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The Changing Tendency and Association Analysis of Intelligent Coal Mines in China: A Policy Text Mining Study

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  • Xiaofang Wo

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Guichen Li

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Yuantian Sun

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China
    State Key Laboratory of Green and Low-Carbon Development of Tar-rich Coal in Western China, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Jinghua Li

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Sen Yang

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Haoran Hao

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

The intellectualization of coal mines provides core technical support for the high-quality development of the coal industry. Intelligent texts, especially intelligent policy documents, play an extremely important role in analyzing the trend of intelligent policies in coal mines. This paper collects more than 50 central and local intelligent coal mine policy texts from recent years. The method of text analysis is a tool used for text mining, and semantic networks are generated; it reflects that the policy mainly focuses on promoting large-scale equipment and platform integration, to promote the overall goal of safe, efficient, and intelligent development of coal mining. By analyzing the high-frequency words of the policy from 2016 to 2022, it reflects that the policy trend mainly goes through the following three stages: firstly, eliminate backward enterprises, encourage coal mine automation and mechanization; then, standardize the basic concept of coal mine intellectualization, carry out the transformation of coal mine intellectualization; and the third stage is to promote the application of key technologies of intellectualization, build intelligent demonstration coal mines and reach the acceptance stage, and promote the further development trend of coal mine intellectualization.

Suggested Citation

  • Xiaofang Wo & Guichen Li & Yuantian Sun & Jinghua Li & Sen Yang & Haoran Hao, 2022. "The Changing Tendency and Association Analysis of Intelligent Coal Mines in China: A Policy Text Mining Study," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11650-:d:916833
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    References listed on IDEAS

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    Cited by:

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    2. Olga Zhironkina & Sergey Zhironkin, 2023. "Technological and Intellectual Transition to Mining 4.0: A Review," Energies, MDPI, vol. 16(3), pages 1-37, February.
    3. Cristina Sáez Blázquez & Vasileios Protonotarios & Max Friedemann & Ignacio Martín Nieto & Katerina Margariti & Diego González-Aguilera, 2025. "Towards the Establishment of Protocols for Defining the Requirements of Different Mining Site Contexts Within the European Project Mine.io," Resources, MDPI, vol. 14(10), pages 1-23, October.
    4. Ningning Chen & Xinqiu Fang & Minfu Liang & Xiaomei Xue & Fan Zhang & Gang Wu & Fukang Qiao, 2023. "Research on Hydraulic Support Attitude Monitoring Method Merging FBG Sensing Technology and AdaBoost Algorithm," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    5. Jicheng Wan & Xuhui Zhang & Chao Zhang & Wenjuan Yang & Mengyu Lei & Yuyang Du & Zheng Dong, 2023. "Vision and Inertial Navigation Combined-Based Pose Measurement Method of Cantilever Roadheader," Sustainability, MDPI, vol. 15(5), pages 1-16, February.

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