テキスト・マイニングとソーシャル・ネットワーク分析に基づく炭鉱事故の危険因子の特定
Guoxun Jing1, Hongli Qin1, Fang Jiang1
1School of Safety Science and Engineering, Henan Polytechnic University, China.
まとめ
この研究は,テキストマイニングとソーシャルネットワーク分析 (SNA) を使用して,石炭鉱山事故の核心と周辺の要因を明らかにしています. 重要なノードに標的を絞った介入は,相互に関連したリスクを管理することによって大きな事故を防ぐことができます.
科学分野:
- 鉱山安全工学
- 事故分析
- ネットワーク科学
背景:
- 伝統的な石炭鉱山事故分析は,複雑な因果関係を把握する上で限界に直面しています.
- 石炭鉱業のリスクが高いため,高度な分析の枠組みが必要です.
研究 の 目的:
- 炭鉱の事故に関する多要素結合分析の枠組みを開発する.
- 核と周辺の因果的要因とその構造的特徴を特定する.
- 鉱山の安全性を高めるための標的型介入戦略を提案する.
主な方法:
- 481件の事故報告から因果的な要因を自動的に抽出するためにテキストマイニングを使用しました.
- 統合されたソーシャルネットワーク分析 (SNA) で,ノードの中心性と伝送強度を定量化します.
- 事故原因システムの"コア・ペリフェリー"構造を分析した.
主要な成果:
- ネットワークハブとして機能する18の主要な因果関係を特定した (例えば,無許可のリスク承受).
- 関連性 (例えば,隠された機器の欠陥) を通じて,コアリスクを拡大する50の周辺的要因を特定した.
- 原因ネットワーク内の"重大な事故を引き起こす小さな信号"のダイナミクスを検証した.
結論:
- 炭鉱における事故の原因は"コア・ペリフェリー"の構造を示し,コア・ファクターは中央のノードとして機能する.
- 外部要因は,コア要因から生じるリスクを大きく影響し,増幅します.
- ネットワーク上の管理と重要なノードでの標的型介入は,単一要素制御よりも鉱山の安全性に対するより効果的なアプローチを提供します.
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