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基于复杂网络理论识别油库关键安全风险因素 被引量:14

Identification of critical safety risk factors in oil depot based on complex network theory
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摘要 为提升油库安全风险管理水平,基于风险因素间关联关系对风险因素重要性的影响,提出从复杂网络角度研究油库安全风险管理并识别关键风险因素的方法。首先,通过识别风险因素并依据因素间的影响关系和影响程度构建油库安全风险加权网络模型;然后,基于风险因素自身的风险水平及其对网络中局部和全局其他因素的影响力,设计风险因素的重要度评价指标;最后,采用层次分析法(AHP)-灰色关联分析(GRA)-理想距离排序(TOPSIS)模型对风险因素重要度进行排序,从而实现关键风险因素的识别。将该方法应用于某油库风险因素识别中。结果表明:人员素质和安全管理风险为该油库关键风险因素。 To improve the level of oil depot safety management, a method was proposed for identifying the most important set of risk factors based on complex network theory and the influence of the correlation be- tween risk factors on their importance. Based on the identification of the safety risk factors, a weighted safety risk network model was built according to the relationship and influence intensity among them. Importance e- valuation criteria of the risk factors were designed based on the risk level and their influence on local and global network. Importance sequencing of those factors was carried out by using the AHP-GRA-TOPSIS mod- el, providing a basis for recognition of the critical factors. A certain oil depot project was taken as an exam- ple, the risk factors in which were identified by using the method. The results show that weakness in per- formance of personnel and that in safety management are the critical risk factors of the oil deport project.
作者 岳希坚 袁永博 张明媛 何祥 YUE Xijian YUAN Yongbo ZHANG Mingyuan HE Xiang(Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian Liaoning 116024, China)
出处 《中国安全科学学报》 CAS CSCD 北大核心 2017年第5期146-151,共6页 China Safety Science Journal
关键词 油库 关键风险因素 复杂网络 层次分析法(AHP) 灰色关联分析(GRA)理想距离排序(TOPSIS) oil depot critical risk factor complex network analytic hierarchy process (AHP) gray relational analysis (GRA) technique for order preference by similarity to an idealsolution (TOPSIS)
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