|本期目录/Table of Contents|

[1]陈志远,王铁骊.基于文本挖掘和复杂网络的事故致因重要度评估方法*——以房屋市政较大以上事故为例[J].中国安全生产科学技术,2022,18(4):224-230.[doi:10.11731/j.issn.1673-193x.2022.04.032]
 CHEN Zhiyuan,WANG Tieli.Evaluation method of accident causes importance based on text mining and complex network:a case study of larger and above accidents in housing and municipal engineering[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(4):224-230.[doi:10.11731/j.issn.1673-193x.2022.04.032]
点击复制

基于文本挖掘和复杂网络的事故致因重要度评估方法*——以房屋市政较大以上事故为例
分享到:

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
18
期数:
2022年4期
页码:
224-230
栏目:
职业安全卫生管理与技术
出版日期:
2022-04-30

文章信息/Info

Title:
Evaluation method of accident causes importance based on text mining and complex network:a case study of larger and above accidents in housing and municipal engineering
文章编号:
1673-193X(2022)-04-0225-07
作者:
陈志远王铁骊
(南华大学 经济管理与法学学院,湖南 衡阳 421001)
Author(s):
CHEN Zhiyuan WANG Tieli
(School of Economics Management and Law.University of South China.Hengyang Hunan 421001,China)
关键词:
事故致因文本挖掘复杂网络房屋市政工程DFn-IG
Keywords:
accident cause text mining complex network housing and municipal engineering DFn-IG
分类号:
X947;TU714
DOI:
10.11731/j.issn.1673-193x.2022.04.032
文献标志码:
A
摘要:
为充分挖掘事故调查报告中的有效信息,明确安全管理工作的内容。首先,利用文本挖掘分析事故调查报告,采用最小词频阈值文档频改进信息增益评估函数对分词结果降噪,通过回溯特征项在报告中的具体表述,提取事故致因,再构建同义词词库。然后,引入复杂网络以改进TF-IDF,综合事故致因因素的关联特征评估其重要度。最后,以房屋市政较大及以上生产安全事故为例,收集2010—2019年事故调查报告158份,研究结果表明:监督管理不到位是导致房屋市政较大以上事故最重要的因素。本方法可用于发现以往事故的原因,更能全面准确地衡量事故致因的重要度。
Abstract:
To fully extract the useful information from the accident investigation reports and clarify the contents of safety management work.firstly.the accident investigation reports were analyzed by using the text mining.and the minimum word frequency threshold document frequency was used to improve the information gain evaluation function so as to denoise the segmentation results.The accident causes were extracted by tracing the specific expression of characteristic items in the report.and the thesaurus of synonyms was constructed.Secondly.the complex network was introduced to improve the TF-IDF.and its importance was evaluated by synthesizing the correlation characteristics of accident cause factors.Finally.taking the larger and above work safety accidents in housing and municipal engineering as example.158 accident investigation reports from 2010 to 2019 were collected.The results showed that the lack of supervision and management was the most important factor leading to the larger and above accidents in housing and municipal engineering.This method can be used to find the causes of previous accidents.and can more comprehensively and accurately measure the importance of accident causes.

参考文献/References:

[1]ZHOU Z,IRIZARRY J.Integrated framework of modified accident energy release model and network theory to explore the full complexity of the hangzhou subway construction collapse[J].Journal of Management in Engineering,2016,32(5):05016013.
[2]邓小鹏,李启明,周志鹏.地铁施工安全事故规律性的统计分析[J].统计与决策,2010(9):87-89. DENG Xiaopeng,LI Qiming,ZHOU Zhipeng.Statistical analysis of the regularity of subway construction safety accidents[J].Statistics & Decision,2010(9):87-89.
[3]郑霞忠,王晓宇,陈述,等.高处坠落事故的人因失误与干预策略研究[J].中国安全生产科学技术,2017,13(6):139-144. ZHENG Xiazhong,WANG Xiaoyu,CHEN Shu,et al.Study on human error and intervention strategies of high falling accidents[J].Journal of Safety Science and Technology,2017,13(6):139-144.
[4]SURAJI A,DUFF A R,PECKITT S J.Development of causal model of construction accident causation[J].Journal of Construction Engineering and Management,2001,127(4):337-344.
[5]GOH Y M,UBEYNARAYANA C U.Construction accident narrative classification:An evaluation of text mining techniques[J].Accident Analysis and Prevention,2017,108:122-130.
[6]ZHONG B,PAN X,LOVE P E D,et al.Hazard analysis:A deep learning and text mining framework for accident prevention[J].Advanced Engineering Informatics,2020,46:101152.
[7]BAHIRUTK,KUMAR SINGH D,TESSFAW EA.Comparative study on data mining classification algorithms for predicting road traffic accident severity \[C\]//2018 Second lnternational Conference on lnventiveCommunication and Computational Technologies(ICICCT).Coimbatore:IEEE,2018:1655-1660.
[8]CAI Q.Cause analysis of traffic accidents on urban roads based on an improved association rule mining algorithm[J].IEEE Access,2020,8:75607-75615.
[9]陈晓云,李荣陆,胡运发.基于最小词频阈值的文档特征选择[J].模式识别与人工智能,2006,19(4):531-537. CHEN Xiaoyun,LI Ronglu,HU Yunfa.Document feature selection based on the minimum term frequency threshold[J].Pattern Recognition and Artificial Intelligence,2006,19(4):531-537.
[10]XU Na,MA Ling,LIU Qing,et al.An improved text mining approach to extract safety risk factors from construction accident reports[J].Safety Science,2021,138:105216.
[11]中华人民共和国住房和城乡建设部.中华人民共和国住房和城乡建设部房屋市政工程生产安全事故情况通报[EB/OL].(2020-03-28)[2021-06-08].https://www.mohurd.gov.cn/.
[12]张伟,朱双娜,张潇,等.建筑施工安全事故致因系统模型与实证分析[J].中国安全科学学报,2019,29(6):56-62. ZHANG Wei,ZHU Shuangna,ZHANG Xiao,et al.Systematic model of construction accident causation and its empirical analysis[J].China Safety Science Journal,2019,29(6):56-62.
[13]HO A B,NOWOBILSKI T,SZER I,et al.Identification of factors affecting the accident rate in the construction industry[J].Procedia Engineering,2017,208:35-42.
[14]TAM C M,ZENG S X,DENG Z M.Identifying elements of poor construction safety management in China[J].Safety Science,2004,42(7):569-586.
[15]MITROPOULOS P,ABDELHAMID T S,HOWELL G A.Systems model of construction accident causation[J].Journal of Construction Engineering and Management,2005,131(7):816-825.
[16]MANU P,ANKRAH N,PROVERBS D,et al.An approach for determining the extent of contribution of construction project features to accident causation[J].Safety Science,2010,48(6):687-692.

相似文献/References:

[1]牛毅,樊运晓,高远.基于数据挖掘的化工生产事故致因主题抽取[J].中国安全生产科学技术,2019,15(10):165.[doi:10.11731/j.issn.1673-193x.2019.10.026]
 NIU Yi,FAN Yunxiao,GAO Yuan.Topic extraction on causes of chemical production accidents based on data mining[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2019,15(4):165.[doi:10.11731/j.issn.1673-193x.2019.10.026]
[2]赵江平,刘小龙,东淑,等.STAMP模型在危化品道路运输事故分析中的应用研究[J].中国安全生产科学技术,2020,16(5):160.[doi:10.11731/j.issn.1673-193x.2020.05.025]
 ZHAO Jiangping,LIU Xiaolong,DONG Shu,et al.Study on application of STAMP model in analysis on road transportation accidents of hazardous chemicals[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(4):160.[doi:10.11731/j.issn.1673-193x.2020.05.025]
[3]费文会.煤矿管理者教育经历与煤矿安全生产关联性分析[J].中国安全生产科学技术,2020,16(7):88.[doi:10.11731/j.issn.1673-193x.2020.07.014]
 FEI Wenhui.Correlation analysis of the coal mine managers’ education experience and work safety of coal mine[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(4):88.[doi:10.11731/j.issn.1673-193x.2020.07.014]
[4]陈芳,陈茜,徐碧晨.基于文本挖掘的管制运行风险主题分析*[J].中国安全生产科学技术,2020,16(11):47.[doi:10.11731/j.issn.1673-193x.2020.11.007]
 CHEN Fang,CHEN Xi,XU Bichen.Analysis on operation risk topics of air traffic control (ATC) based on text mining[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(4):47.[doi:10.11731/j.issn.1673-193x.2020.11.007]
[5]黄麟淇,吴欣,王秉,等.宏安全视域下重大传染病防控模型构建研究*[J].中国安全生产科学技术,2021,17(10):11.[doi:10.11731/j.issn.1673-193x.2021.10.002]
 HUANG Linqi,WU Xin,WANG Bing,et al.Research on model construction of major infectious diseases prevention and control from perspective of macro security[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(4):11.[doi:10.11731/j.issn.1673-193x.2021.10.002]
[6]陈农田,李俊辉,满永政,等.基于民航安全信息文本挖掘的进近着陆致险因素分析*[J].中国安全生产科学技术,2022,18(3):5.[doi:10.11731/j.issn.1673-193x.2022.03.001]
 CHEN Nongtian,LI Junhui,MAN Yongzheng,et al.Risk factors analysis of approach and landing based on civil aviation safety information text mining[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(4):5.[doi:10.11731/j.issn.1673-193x.2022.03.001]
[7]牟庆泉,丁小兵,刘志钢,等.基于地铁运营日志文本挖掘的危险源辨识算法研究*[J].中国安全生产科学技术,2022,18(3):204.[doi:10.11731/j.issn.1673-193x.2022.03.031]
 MU Qingquan,DING Xiaobing,LIU Zhigang,et al.Research on identification algorithm of hazard sources based on text mining of metro operation log[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(4):204.[doi:10.11731/j.issn.1673-193x.2022.03.031]
[8]李华,孔娇.基于文本挖掘的城市景区密集人群风险感知*[J].中国安全生产科学技术,2022,18(5):40.[doi:10.11731/j.issn.1673-193x.2022.05.006]
 LI Hua,KONG Jiao.Risk perception of dense crowd in urban scenic spots based on text mining[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(4):40.[doi:10.11731/j.issn.1673-193x.2022.05.006]
[9]万程鹏,刘翼飞,吴兵,等.基于复杂网络的水上交通风险辨识及事故演化机理研究*[J].中国安全生产科学技术,2023,19(8):165.[doi:10.11731/j.issn.1673-193x.2023.08.024]
 WAN Chengpeng,LIU Yifei,WU Bing,et al.Study on risk identification and accident evolution mechanism of maritime traffic accidents based on complex network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(4):165.[doi:10.11731/j.issn.1673-193x.2023.08.024]

备注/Memo

备注/Memo:
收稿日期: 2021-07-10
* 基金项目: 湖南省教育厅重点项目(19A438);湖南省社科基金项目(19JD56)
作者简介: 陈志远,硕士研究生,主要研究方向为数据挖掘与安全管理。
通信作者: 王铁骊,博士,教授,主要研究方向为数据挖掘与安全文化。
更新日期/Last Update: 2022-05-13