风险评估
船员
贝叶斯网络
风险分析(工程)
中国
层次分析法
计算机科学
环境资源管理
运输工程
环境规划
环境科学
工程类
业务
运筹学
计算机安全
地理
人工智能
考古
航空学
作者
Guoqing Xia,Xinjian Wang,Yinwei Feng,Yuhao Cao,Zhichao Dai,Huanxin Wang,Zhengjiang Liu
出处
期刊:ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
[American Society of Civil Engineers]
日期:2023-10-16
卷期号:9 (4)
被引量:18
标识
DOI:10.1061/ajrua6.rueng-1158
摘要
Compared with ocean transportation, inland waterway transportation (IWT) has issues such as a low configuration standard of navigation equipment, insufficient crew knowledge and skills, and the relatively more complex hydrographic environment of inland waterways. To recognize and quantify the risk of IWT, this study proposes a novel risk assessment method. Firstly, text mining by Python is applied to recognize the risk influential factors (RIFs) from marine accident investigation reports (MAIRs), and a risk evaluation hierarchy system is established. Secondly, a risk assessment model which integrates failure mode and effects analysis (FMEA), a belief rule-based Bayesian network (BRBN) and evidential reasoning (ER) is proposed to quantify the risk level of influential factors. Finally, a case study of the Songhua River was carried out to verify the feasibility and practicality of the established risk evaluation index system and research methods. The targeted preventive measures are proposed to improve the safety of IWT. This study shows that misobservation and poor safety awareness are the most important human factors affecting the safety of IWT, whereas the organizational factors have relatively low risk priority. It is suggested that stakeholders should strengthen the assessment of crew members and improve their ability to recognize hazards.
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