习惯性违章行为耦合关联分析模型

doi:10.16265/j.cnki.issn1003-3033.2017.02.006

中国安全科学学报 ›› 2017, Vol. 27 ›› Issue (2): 30-35.doi: 10.16265/j.cnki.issn1003-3033.2017.02.006

习惯性违章行为耦合关联分析模型

孙劲光^1,2 教授, 刘露¹, 牛莉霞³ 副教授

1 辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛 125105
2 辽宁省数字化矿山装备工程技术研究中心,辽宁阜新 123000
3 辽宁工程技术大学工商管理学院,辽宁葫芦岛 125105

收稿日期:2016-11-19 修回日期:2017-01-24 出版日期:2017-02-28 发布日期:2020-11-22
通讯作者: 牛莉霞,(1983—),女,山西吕梁人,博士,副教授,主要从事组织行为、安全管理与系统工程方面的教学、科研工作。E-mail:nlx8941@126.com。
作者简介:孙劲光 (1962—),女,辽宁阜新人,博士,教授,主要从事知识工程、计算机图形学以及图像工程方面的研究。E-mail:sunjinguang@lntu.edu.cn。
基金资助:
国家自然科学基金青年项目资助(51504126,51404125);辽宁省教育厅项目资助(LJYR007)。

Couplinganalysis model for habitual violation behavior

SUN Jinguang^1,2, LIU Lu¹, NIU Lixia³

1 School of Electronic and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China
2 Liaoning Digital Mining Equipment Engineering Technology Research Center, Fuxin Liaoning 123000, China
3 School of Business Management, Liaoning Technical University, Huludao Liaoning 125105, China

Received:2016-11-19 Revised:2017-01-24 Online:2017-02-28 Published:2020-11-22

摘要/Abstract

摘要： 为探讨习惯性违章行为(HVB)的属性间与属性内的关系特征,建立习惯性违章行为的耦合关联分析模型。首先,分析违章行为属性值的分布特征及关联关系,运用关联规则(ARM)挖掘思想和耦合关系理论对各类违章行为下相应属性的关联系数进行求解,得到一个耦合关联度向量集,且对诸向量从大到小排序;然后,依据排序后耦合关联度向量集映射成习惯性违章行为耦合关联分析模型。最后,引入召回率、精确率和平均绝对值误差(MAE)等3个指标,分别求解数据集和模型的指标结果。所建模型与ARM分析结果的对比表明,模型在习惯性违章行为关联关系分析的准确性与全面性方面都效果良好。

关键词: 习惯性违章行为, 关联规则(ARM)挖掘思想, 耦合关系, 关系特征分析, 耦合关联分析模型

Abstract: In order to explore the relational characteristics between and within the attributes of HVB, a coupling association analysis model of HVB should be built. Firstly, distribution characteristics and association relationships of the violation attribute values were analyzed. The correlation coefficients of the corresponding attributes under various violations were obtained by using the ARM and coupling relation theory. A set of coupling correlation degree vectors, meanwhile, was obtained,and the vectors were ranked from large to small. And then, according to the sorted coupling correlation degree vector set, the coupling association analysis model of HVB was mapped. In the end, 3 indicators, recall rate, precision rate and mean absolute error (MAE) were introduced to solve the indicators results of the data set and the model. A comparison was made between the model and ARM analysis results.The result shows that the model performs well in accuracy and comprehensiveness for habitual violation behavior's association relationship analysis.

Key words: habitual violations, association rules management (ARM) thought, coupling relation, analysis of relational characteristics, coupling association analysis model

中图分类号:

X913.4

孙劲光, 刘露, 牛莉霞. 习惯性违章行为耦合关联分析模型[J]. 中国安全科学学报, 2017, 27(2): 30-35.

SUN Jinguang , LIU Lu , NIU Lixia. Couplinganalysis model for habitual violation behavior[J]. China Safety Science Journal, 2017, 27(2): 30-35.

参考文献

[1] CAO Longbing. Behavior informatics: a new perspective[J]. Intelligent Systems IEEE, 2014, 29(4):62-80.
[2] 陈红, 祁慧, 汪鸥,等. 中国煤矿重大事故中故意违章行为影响因素结构方程模型研究[J]. 系统工程理论与实践, 2007, 27(8):127-136.
CHEN Hong,QI Hui,WANG Ou,et al.The research on the structural equation model of affecting factors of deliberate violation in coal mine fatal accidents in China[J].Systems Engineering-Theory & Practice,2007,27(8):127-136.
[3] 陈红, 祁慧, 谭慧. 基于特征源与环境特征的中国煤矿重大事故研究[J]. 中国安全科学学报, 2005, 15(9):33-38.
CHEN Hong,QI Hui,TAN Hui.Study on fatal accidents in China's coal mines based on feature sources and environment characters[J].China Safety Science Journal,2005, 15(9):33-38.
[4] 牛莉霞, 刘谋兴, 李乃文,等. 基于ABMS的矿工习惯性违章行为演化仿真[J]. 中国安全科学学报, 2015,25(11):34-40.
NIU Lixia,LIU Mouxing,LI Naiwen,et al.Simulation of evolution miners's habitual violation behavior based on ABMS[J].China Safety Science Journal,2015,25(11):34-40.
[5] 李乃文, 徐梦虹, 牛莉霞. 基于ISM和AHP法的矿工习惯性违章行为影响因素研究[J]. 中国安全科学学报, 2012, 22(8):22-28.
LI Naiwen,XU Menghong,NIU Lixia.Study on factors influence miners' habitual violation behavior based on ISM and AHP[J].China Safety Science Journal,2012,22(8):22-28.
[6] HOFMANN D A,STETZER A. A cross-level investigation of factors influencing unsafe behaviors and accidents[J]. Personnel Psychology, 1996, 49(2):307-339.
[7] RUNDMO T,HESTAD H,ULLEBERG P. Organisational factors, safety attitudes and workload among offshore oil personnel[J]. Safety Science, 1998, 29(2):75-87.
[8] RAKESH Agrawal . Mining association rules between sets of items in large databases[J]. Acm Sigmod Record, 1999, 22(2):207-216.
[9] BERNARD Kamsufoguem,FABIEN Rigal,FELIX Mauget. Mining association rules for the quality improvement of the production process[J]. Expert Systems with Applications, 2013, 40(4):1 034-1 045.
[10] ZAKI Mohammed J.Scalable algorithms for association mining[J]. IEEE Transactions on Knowledge & Data Engineering, 2000, 12(3):372-390.
[11] WANG Can, CAO Longbing,LI Jinjiu,et al. Coupled nominal similarity in unsupervised learning[C].ACM Conference on Information and Knowledge Management(CIKM 2011), 2011:973-978.
[12] CAO Longbing . Non-IIDness learning in behavioral and social data[J]. Computer Journal, 2013, 57(9):1 358-1 370.
[13] CAO Longbing , YU Ouming, PHILIP S Yu . Coupled behavior analysis with applications[J]. IEEE Transactions on Knowledge & Data Engineering, 2012, 24(8):1 378-1 392.
[14] 余永红, 陈兴国, 高阳. 一种基于耦合对象相似度的项目推荐算法[J]. 计算机科学, 2014, 41(2):33-35.
YU Yonghong,CHEN Xinguo,GAO Yang.Coupled object similarity based item recommendation algorithm[J].Computer Science,2014,41(2):33-35.
[15] 郭梦娇, 孙劲光, 孟祥福. 基于耦合相似度的矩阵分解推荐方法[J]. 计算机科学, 2016, 43(4):247-251.
GUO Mengjiao,SUN Jinguang,MENG Xiangfu.Coupling similarity-based matrix factorization technique for recommendation[J].Computer Science,2016,43(4):247-251.

习惯性违章行为耦合关联分析模型

Couplinganalysis model for habitual violation behavior

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 6

编辑推荐

Metrics

本文评价

[1]	贺莹鸽, 连民杰, 江松, 苏梦哲. 矿工习惯性违章行为风险态势评估[J]. 中国安全科学学报, 2020, 30(12): 62-69.
[2]	刘钰欣, 栗继祖, 冯国瑞, 康立勋. 基于改进CPT的矿工HVB变化分析[J]. 中国安全科学学报, 2017, 27(7): 13-17.
[3]	牛莉霞, 刘谋兴, 李乃文, 黄敏. HVB惯性度的MPHMADM评价[J]. 中国安全科学学报, 2017, 27(7): 48-52.
[4]	牛莉霞，李乃文，姜群山. 习惯性违章行为变革驱动力模型构建[J]. 中国安全科学学报, 2014, 24(1): 28-.
[5]	陈曦，葛少成. 基于Fluent软件的高压喷雾捕尘技术数值模拟与应用[J]. 中国安全科学学报, 2013, 23(8): 144-.
[6]	李乃文，徐梦虹，牛莉霞. 基于ISM和AHP法的矿工习惯性违章行为影响因素研究[J]. 中国安全科学学报, 2012, 22(8): 22-.