基于文本聚类的煤矿安全隐患类型挖掘研究
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摘要
为提升煤矿安全管理者对隐患数据的理解和处理能力,提高隐患排查治理工作水平,将文本聚类方法运用于煤矿企业历史安全隐患记录数据的挖掘分析,并采用卡方统计量提取与类别关联度高的特征词描述聚类结果,研究历史隐患数据中记录的主要隐患的类型及特点。结果表明:文本聚类与卡方统计相结合,能够有效识别煤矿安全隐患数据中记录的主要隐患类型及特点;隐患排查治理工作应以数量多的隐患类型作为排查侧重点,根据隐患类型的特点制定相应的治理措施,以改善隐患排查治理工作的针对性和有效性。
In order to enhance the ability of coal mine safety administrators to understand and process hidden danger data,and improve the work of hidden danger investigation and management,the text clustering method was applied to mining and analyzing the data of historical safety hazards records of coal mining enterprises.The chi-square statistics was used to extract feature words,and the feature words with high degree of correlation with category were used to describe the clustering results. The main types and characteristics of hidden dangers recorded in historical data were studied. The results show that the combination of text clustering and chi-square statistics could identify the types and characteristics of the main hidden dangers recorded in the data on coal mine safety hazards and that the serctor in coal mine responsible for investigation and treatment of hidden dangers should focus on the hidden danger types with large numbers,and formulate corresponding treatment measures according to the characteristics of hidden danger types,so as to improve the pertinence and effectiveness of the investigation and treatment of hidden dangers.
In order to enhance the ability of coal mine safety administrators to understand and process hidden danger data,and improve the work of hidden danger investigation and management,the text clustering method was applied to mining and analyzing the data of historical safety hazards records of coal mining enterprises.The chi-square statistics was used to extract feature words,and the feature words with high degree of correlation with category were used to describe the clustering results. The main types and characteristics of hidden dangers recorded in historical data were studied. The results show that the combination of text clustering and chi-square statistics could identify the types and characteristics of the main hidden dangers recorded in the data on coal mine safety hazards and that the serctor in coal mine responsible for investigation and treatment of hidden dangers should focus on the hidden danger types with large numbers,and formulate corresponding treatment measures according to the characteristics of hidden danger types,so as to improve the pertinence and effectiveness of the investigation and treatment of hidden dangers.
引文
[1]吴大明.煤矿安全隐患概念辨析与双重预防机制应用研究[J].中国煤炭,2017,43(9):112-115.WU Daming. Study on the concept of loopholes in coal mine safety and the application of double prevention mechanism[J].China Coal,2017,43(9):112-115.
[2]张长鲁.煤矿事故隐患大数据处理与知识发现分析方法研究[J].中国安全生产科学技术,2016,12(9):176-181.ZHANG Changlu.Study on big data processing and knowledge discovery analysis method for safety hazard in coal mine[J].Journal of Safety Science and Technology,2016,12(9):176-181.
[3]张长鲁,侯军岐.基于T型关联度的煤矿隐患与煤炭开采关系研究[J].煤矿安全,2016,47(5):235-237.ZHANG Changlu,HOU Junqi.Study on coal minesproduction and hidden danger based on T-type correlation degree[J].Safety in Coal Mines,2016,47(5):235-237.
[4]谭章禄,王泽,陈晓.基于LDA的煤矿安全隐患主题发现研究[J].中国安全科学学报,2016,26(6):123-128.TAN Zhanglu,WANG Ze,CHEN Xiao.Research on topic extraction for coal mine hidden danger based on LDA[J].China Safety Science Journal,2016,26(6):123-128.
[5]谭章禄,陈晓,宋庆正,等.基于文本挖掘的煤矿安全隐患分析[J].安全与环境学报,2017,17(4):1 262-1 266.TAN Zhanglu,CHEN Xiao,SONG Qingzheng,et al. Analysis for the potential hazardous risks of the coal mines based on the socalled text mining[J].Journal of Safety and Environment,2017,17(4):1 262-1 266.
[6]陈运启.数据挖掘技术在煤矿隐患管理中的应用[J].工矿自动化,2016,42(2):27-30.CHEN Yunqi. Application of data mining technology in coal mine hidden hazard management[J]. Industry and Mine Automation,2016,42(2):27-30.
[7]张大伟.基于OLAM的煤矿企业安全隐患趋势分析[J].煤炭工程,2015,47(5):139-142.ZHANG Dawei.Analysis of coal mine safety hidden danger trends based on OLAM[J]. Coal Engineering,2015,47(5):139-142.
[8]刘双跃,杨蕾,彭丽.基于改进Apriori算法的煤矿物态隐患系统设计与应用[J].煤炭技术,2015,34(4):318-320.LIU Shuangyue,YANG Lei,PENG Li. Design and application of coal mine state hidden danger system based on data mining[J].Coal Technology,2015,34(4):318-320.
[9]中华人民共和国国务院.煤矿安全监察条例[L].2000-11-07.
[10]国家煤矿安全监察局.煤矿安全规程[L].2016-02-25.
[2]张长鲁.煤矿事故隐患大数据处理与知识发现分析方法研究[J].中国安全生产科学技术,2016,12(9):176-181.ZHANG Changlu.Study on big data processing and knowledge discovery analysis method for safety hazard in coal mine[J].Journal of Safety Science and Technology,2016,12(9):176-181.
[3]张长鲁,侯军岐.基于T型关联度的煤矿隐患与煤炭开采关系研究[J].煤矿安全,2016,47(5):235-237.ZHANG Changlu,HOU Junqi.Study on coal minesproduction and hidden danger based on T-type correlation degree[J].Safety in Coal Mines,2016,47(5):235-237.
[4]谭章禄,王泽,陈晓.基于LDA的煤矿安全隐患主题发现研究[J].中国安全科学学报,2016,26(6):123-128.TAN Zhanglu,WANG Ze,CHEN Xiao.Research on topic extraction for coal mine hidden danger based on LDA[J].China Safety Science Journal,2016,26(6):123-128.
[5]谭章禄,陈晓,宋庆正,等.基于文本挖掘的煤矿安全隐患分析[J].安全与环境学报,2017,17(4):1 262-1 266.TAN Zhanglu,CHEN Xiao,SONG Qingzheng,et al. Analysis for the potential hazardous risks of the coal mines based on the socalled text mining[J].Journal of Safety and Environment,2017,17(4):1 262-1 266.
[6]陈运启.数据挖掘技术在煤矿隐患管理中的应用[J].工矿自动化,2016,42(2):27-30.CHEN Yunqi. Application of data mining technology in coal mine hidden hazard management[J]. Industry and Mine Automation,2016,42(2):27-30.
[7]张大伟.基于OLAM的煤矿企业安全隐患趋势分析[J].煤炭工程,2015,47(5):139-142.ZHANG Dawei.Analysis of coal mine safety hidden danger trends based on OLAM[J]. Coal Engineering,2015,47(5):139-142.
[8]刘双跃,杨蕾,彭丽.基于改进Apriori算法的煤矿物态隐患系统设计与应用[J].煤炭技术,2015,34(4):318-320.LIU Shuangyue,YANG Lei,PENG Li. Design and application of coal mine state hidden danger system based on data mining[J].Coal Technology,2015,34(4):318-320.
[9]中华人民共和国国务院.煤矿安全监察条例[L].2000-11-07.
[10]国家煤矿安全监察局.煤矿安全规程[L].2016-02-25.