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[1]周翔,马利宁,马新根,等.基于链路预测的煤矿事故隐患文本分析研究*[J].中国安全生产科学技术,2024,20(12):26-34.[doi:10.11731/j.issn.1673-193x.2024.12.004]
　ZHOU Xiang,MA Lining,MA Xingen,et al.Research on text analysis of hidden dangers of coal mine accidents based on link prediction[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2024,20(12):26-34.[doi:10.11731/j.issn.1673-193x.2024.12.004]
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基于链路预测的煤矿事故隐患文本分析研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
20
期数:
2024年12期
页码:
26-34
栏目:
学术论著
出版日期:
2024-12-30

文章信息/Info

Title:
Research on text analysis of hidden dangers of coal mine accidents based on link prediction
文章编号:
1673-193X(2024)-12-0026-09
作者:
周翔; 马利宁; 马新根; 郝强; 贾海钰; 刘辉; 白文兴; 张宏智; 李圣江; 杨起凡
（1.华能煤业有限公司陕西矿业分公司，陕西 西安 710000；
2.华能煤业有限公司，北京 100070；
3.华能煤炭技术研究有限公司，北京 100070；
4.中国矿业大学(北京） 能源与矿业学院，北京 100083；
5.华亭煤业集团有限责任公司，甘肃 平凉 744100；
6.扎赉诺尔煤业有限责任公司，内蒙古 满洲里 021410；
7.庆阳新庄煤业有限公司新庄煤矿，甘肃 庆阳 745000；
8.华能云南滇东能源有限责任公司矿业分公司，云南 曲靖 655508）
Author(s):
ZHOU Xiang;  MA Lining;  MA Xin’gen;  HAO Qiang;  JIA Haiyu;  LIU Hui;  BAI Wenxing;  ZHANG Hongzhi;  LI Shengjiang;  YANG Qifan
(1.Shaanxi Mining Branch of Huaneng Coal Industry Co.,Ltd.;
2.Huaneng Coal Industry Co.,Ltd.;
3.Huaneng Coal Technology Research Co.,Ltd.;
4.School of Energy and Mining Engineering,China University of Mining and Technology (Beijing);
5.Huating Coal Industry Group Co.,Ltd.;
6.Zalainuoer Coal Industry Co.,Ltd. ;
7.Xinzhuang Coal Mine of Qingyang Xinzhuang Coal Industry Co.,Ltd.;
8.Huaneng Yunnan Diandong Energy Co.,Ltd.Mining Branch)
关键词:
煤矿安全; 隐患排查; 数据挖掘; 链路预测; 关联规则
Keywords:
coal mine safety;  hidden danger identification;  data mining;  link prediction;  association rule
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2024.12.004
文献标志码:
A
摘要:
为有效从海量文本数据中挖掘有价值的煤矿事故隐患信息并进行预测，基于某煤矿生产过程中产生的安全隐患预处理文本进行研究，利用链路预测方法来探寻煤矿事故隐患文本的关联规则，提出1种RA与RWR相结合的局部随机游走指标进行研究。研究结果表明：改进后的指标在较高的移除比例范围内拥有优于局部相似性方法的精度，且其计算效率明显优于全局随机游走指标；通过分析关键词共现关系，验证了改进的链路预测方法的准确性，并成功预测出部分未来存在但当前未产生的节点关系。研究结果可为煤矿安全生产管理提供1种新的方法和工具，有利于提升煤矿的安全生产水平。
Abstract:
In order to effectively mine the valuable coal mine accident hidden danger information from massive text data and conduct prediction,the pre-processing text of safety hidden danger generated in the production process of a certain coal mine was studied.The link prediction method was used to explore the association rules of coal mine accident hidden danger texts,and a local random walk index combining RA and RWR was proposed.The results show that the improved index has better accuracy than the local similarity method within a higher removal ratio range,and its calculation efficiency is significantly better than the global random walk index.By analyzing the co-occurrence relationship of keywords,the accuracy of the improved link prediction method is verified,and some node relationships that exist in future but have not yet been generated at present are successfully predicted.The research results can provide a new method and tool for work safety management in coal mines,which is conducive to improve the work safety level of coal mines.

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备注/Memo

备注/Memo:
收稿日期： 2024-02-26
* 基金项目： 中国华能集团有限公司总部科技项目（HNKJ20-H33）
作者简介： 周翔，硕士，高级工程师，主要研究方向为采矿工程领域。
通信作者： 马新根，博士，高级工程师，主要研究方向为智慧矿山领域。
更新日期/Last Update: 2024-12-28