Resilience Assessment for the Northern Sea Route Based on a Fuzzy Bayesian Network

被引:18
|
作者
Qiao, Weiliang [1 ]
Ma, Xiaoxue [2 ]
Liu, Yang [3 ]
Lan, He [3 ]
机构
[1] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Peoples R China
[2] Dalian Maritime Univ, Publ Adm & Humanities Coll, Dalian 116026, Peoples R China
[3] Dalian Maritime Univ, Sch Maritime Econ & Management, Dalian 116026, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 08期
关键词
northern sea route; resilience assessment; Bayesian network; fuzzy theory;
D O I
10.3390/app11083619
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The safety level of the northern sea route (NSR) is a common concern for the related stakeholders. To address the risks triggered by disruptions initiating from the harsh environment and human factors, a comprehensive framework is proposed based on the perspective of resilience. Notably, the resilience of NSR is decomposed into three capacities, namely, the absorptive capacity, adaptive capacity, and restorative capacity. Moreover, the disruptions to the resilience are identified. Then, a Bayesian network (BN) model is established to quantify resilience, and the prior probabilities of parent nodes and conditional probability table for the network are obtained by fuzzy theory and expert elicitation. Finally, the developed Bayesian networkBN model is simulated to analyze the resilience level of the NSR by back propagation, sensitivity analysis, and information entropy analysis. The general interpretation of these analyses indicates that the emergency response, ice-breaking capacity, and rescue and anti-pollution facilities are the critical factors that contribute to the resilience of the NSR. Good knowledge of the absorptive capacity is the most effective way to reduce the uncertainty of NSR resilience. The present study provides a resilience perspective to understand the safety issues associated with the NSR, which can be seen as the main innovation of this work.
引用
收藏
页数:28
相关论文
共 50 条
  • [21] A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
    Xu, Sheng
    Kim, Ekaterina
    Haugen, Stein
    Zhang, Mingyang
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 223
  • [22] Resilience assessment of a subsea pipeline using dynamic Bayesian network
    Yazdi, Mohammad
    Khan, Faisal
    Abbassi, Rouzbeh
    Quddus, Noor
    JOURNAL OF PIPELINE SCIENCE AND ENGINEERING, 2022, 2 (02):
  • [23] Evaluation of the factors causing container lost at sea through fuzzy-based Bayesian network
    Oztuerk, Orkun Burak
    REGIONAL STUDIES IN MARINE SCIENCE, 2024, 73
  • [24] Risk Assessment of Bauxite Maritime Logistics Based on Improved FMECA and Fuzzy Bayesian Network
    Sun, Jiachen
    Wang, Haiyan
    Wang, Mengmeng
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (04)
  • [25] Risk assessment of gas explosion in coal mines based on fuzzy AHP and bayesian network
    Li, Min
    Wang, Hetang
    Wang, Deming
    Shao, Zhenlu
    He, Shan
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2020, 135 : 207 - 218
  • [26] Research on Safety Risk Assessment of Construction of Large Formwork Based on Fuzzy Bayesian Network
    Peng, Yijing
    PROCEEDINGS OF THE 2017 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTER (MACMC 2017), 2017, 150 : 73 - 79
  • [27] Risk assessment of gas explosion in coal mines based on fuzzy AHP and bayesian network
    Li M.
    Wang H.
    Wang D.
    Shao Z.
    He S.
    Process Safety and Environmental Protection, 2020, 135 : 207 - 218
  • [28] Risk assessment of railway dangerous goods transport rocess based on fuzzy Bayesian Network
    Yang, Neng-Pu
    Yang, Yue-Fang
    Feng, Wei
    Tiedao Xuebao/Journal of the China Railway Society, 2014, 36 (07): : 8 - 15
  • [29] DEVELOPING A COMPREHENSIVE RISK ASSESSMENT MODEL BASED ON FUZZY BAYESIAN BELIEF NETWORK (FBBN)
    Guan, Li
    Liu, Qiang
    Abbasi, Alireza
    Ryan, Michael J.
    JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, 2020, 26 (07) : 614 - 634
  • [30] Fire risk assessment in cotton storage based on fuzzy comprehensive evaluation and Bayesian network
    Chen, Jinyue
    Ji, Jie
    Ding, Long
    Wu, Jiansong
    FIRE AND MATERIALS, 2020, 44 (05) : 683 - 692