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

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Area of Science:

  • Mining Engineering
  • Safety Science
  • Data Mining

Background:

  • Coal mine accident risk increases with depth, necessitating scientific analysis and advanced technologies for prevention.
  • Understanding research progress and focus differences in coal mine accidents is crucial for improving disaster management and prevention.
  • Global research on coal mine accidents is predominantly published in Chinese or English.

Purpose of the Study:

  • To analyze the research progress and focus differences in coal mine accident studies between China and other countries.
  • To identify shortcomings in current research and promote more effective coal mine disaster management.
  • To enhance the prevention and control capabilities for coal mine accidents.

Main Methods:

  • Analysis of Chinese and foreign literature on coal mine accidents.
  • Application of data mining algorithms, specifically Latent Semantic Indexing (LSI) and Apriori.
  • Comparative analysis of research trends, author contributions, and thematic focuses.

Main Results:

  • Chinese authors dominate coal mine accident research, contributing over 81% of authors.
  • Chinese studies focus on macro-scale accident patterns and causes, while English studies concentrate on occupational injuries and specific disaster mechanisms.
  • Chinese research increasingly incorporates AI for deep mining safety since 2018, while English research hotspots remain consistent.
  • Both Chinese and English studies explored 'public opinion' around 2019, with differing focuses on government guidance versus critical analysis.

Conclusions:

  • China leads global research in coal mine accident prevention and control, with a distinct focus on technological integration and macro-level analysis.
  • Divergent research priorities between Chinese and English literature highlight opportunities for knowledge exchange and collaborative advancement.
  • The evolution of Chinese research reflects the country's industrial development and policy shifts, particularly the adoption of AI in deep mining safety.