贝叶斯网络
海底管道
条件概率
计算机科学
模糊逻辑
节点(物理)
风险评估
模糊集
集合(抽象数据类型)
工程类
灵敏度(控制系统)
数据挖掘
运筹学
可靠性工程
海洋工程
人工智能
统计
数学
计算机安全
岩土工程
结构工程
电子工程
程序设计语言
作者
Zhenshuang Wang,Yanxin Zhou,Tao Wang
出处
期刊:IEEE Transactions on Engineering Management
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:: 1-14
标识
DOI:10.1109/tem.2023.3327436
摘要
Oil spill accidents on offshore platforms will cause serious environmental damage and huge economic losses. In this research, the offshore platform system is divided into six subsystems: “Human,” “Production and Storage,” “Special ship,” “Operation platform,” “Environment,” and “Management.” Combined with the historical data of oil spill accidents and the cause flow chart of accidents, the dynamic risk assessment method of offshore platform systems is constructed with the Bayesian network. First, the Dempster–Shafer evidence theory method is used to obtain the prior probability value of nodes, based on using the fuzzy set method to determine the prior probability value given by experts. Second, the Noisy-Max/Min algorithm is used to determine the conditional probability, and the risk node sensitivity is determined by combining the model. Finally, the model is verified by the receiver operating characteristic curve. The results show that the area under curve of the model is 0.870, which verifies the feasibility and effectiveness of the proposed method.
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