基于事故报告挖掘的矿工不安全行为管控

吕月颖; 季嘉琪; 陈修杰; 王文浩; 苗德俊

基于事故报告挖掘的矿工不安全行为管控

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出版历程
- 发布日期: 2023-02-19

Unsafe behavior control of miners based on accident reporting excavation

摘要

摘要: 人因是诱发煤矿事故的重要致因，为研究人因事故中的规律性，并提高人因治理的针对性；采用文本数据挖掘的方法，依照事故诱发机制，对事故报告文本数据进行WordCloud-LDA分析，构建了煤矿事故人因因素体系；在此基础上，生成煤矿事故人因矩阵集，并对人因矩阵集进行关联分析，得出人因因素与一般事故、顶板事故间的强关联规则。结果表明：事故报告挖掘下煤矿人因关联规则研究可以得出人因因素间趋势性的结论，为人因管控决策提供依据和基础。
- 事故挖掘 /
- 文本分析 /
- WordCloud-LDA分析 /
- Apriori算法 /
- 强关联规则
Abstract: Human factor is an important cause of coal mine accidents. In order to study the regularity in human-caused accidents and to improve the target of human-caused management, text data mining method was used to analyze the accident report text data by WordCloud-LDA according to the accident triggering mechanism, and to construct a human-caused factor system for coal mine accidents. On this basis, the human factor matrix set of coal mine accidents is generated, and the correlation analysis of the human factor matrix set is carried out, and the strong association rules between the human factor and the general accident and the roof accident are obtained. The results show that the study of human factors association rules in coal mines under accident report mining can lead to conclusions on the trend among human factors, and provide a basis for human factors control decisions.
- incident mining /
- text analysis /
- WordCloud-LDA analysis /
- Apriori algorithm /
- strong association rules

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参考文献(10)

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