Using DBN and evidence-based reasoning to develop a risk performance model to interfere ship navigation process safety in Arctic waters

Li, Zhuang; Hu, Shenping; Zhu, Xiaoming; Gao, Guoping; Yao, Chenyang; Han, Bing

doi:10.1016/j.psep.2022.03.089

Cited by 29 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Xuan et al [30] proposed a complete node model based on the risk analysis of LNG bunkering operations, established a system dynamics model based on the catastrophe theory, and simulated the risk evolution of a ship bunkering process. Li et al [31] built a DBN model together with the Dempster-Shafer (D-S) evidence theory and cloud models to integrate expert judgment, marine meteorological data, and monitoring data to infer the risk evolution of an LNG vessel running in arctic waters. With the complex coupling of the environment, ship equipment and operators in a ship pilotage operations process [3], the system risk performance presents a spatiotemporal change, that is, the risk evolution of the operation process.…”

Section: Maritime Risk Analysis and Risk Evolution Analysismentioning

confidence: 99%

“…Qian et al [44] evaluated the dynamic natural environment risk of the key nodes in the Arctic Northwest Passage by constructing a DBN through index selection and data processing under a ship navigation scenario. DBN can synthesize observational data, expert knowledge and simulation data, and combine the transition probabilities of dynamic factors to realize the temporal inference of system risk [31]. It is revealed that DBN is suitable to the inference of risk evolution in ship operations.…”

Section: Maritime Risk Analysis Using Bn and Dbnmentioning

confidence: 99%

See 1 more Smart Citation

Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN

Guo

Jin

et al. 2023

Reliability Engineering & System Safety

Self Cite

View full text Add to dashboard Cite

Section: Maritime Risk Analysis and Risk Evolution Analysismentioning

confidence: 99%

Section: Maritime Risk Analysis Using Bn and Dbnmentioning

confidence: 99%

Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN

Guo

Jin

et al. 2023

Reliability Engineering & System Safety

Self Cite

View full text Add to dashboard Cite

“…According to formula (2), the expert evaluation table can be combined into the comprehensive risk evaluation table of risk source, and then the table can be sorted into a standardized triangular IFN risk evaluation matrix by using the standardized formula (5).…”

Section: Decision Algorithm Based On Improved Fuzzymentioning

confidence: 99%

“…Over the years, ship safety has always been an important research topic and content in the international shipping feld and has always been the work of shipping units and maritime management departments at home and abroad. Its risk assessment is a complex system engineering, which is not only afected by the static and dynamic information of the ship itself, but also involves the operation task, personnel allocation, policies and regulations, and the uncertain information of navigation waters to a certain extent [4,5]. At the same time, the assessment process is also contingent on the subjectivity of experts and limited statistics, increasing the fuzziness and uncertainty of ship risk assessment [6].…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment Method for Ship Based on Improved Fuzzy Multicriteria Decision-Making

Wang

Xie

Zeng

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Aimed at the uncertainties and relevance issues during the risk factor identification in multicriteria decision-making, this paper presents a ship risk assessment model based on the improved fuzzy multicriteria decision-making. First, on the basis of safety assessment and importance judgment of risk sources conducted by experts, the peer-to-peer consensus model is employed to integrate the relative importance of risk sources and obtain the weight of experts; the weight of risk factors is then determined by nonlinear programming model according to the experts’ preference for risk sources; finally, the risk assessment is carried out using the MULTIMOORA method and the final ranking of the alternatives is determined by means of the fuzzy number quantitative calculation method. Analysis and research are conducted on specific causes of ship engine room fires, and the results are compared with outcomes of the traditional MULTIMOORA method and the fuzzy analytic hierarchy process based on Monte Carlo simulation. It is concluded that the calculated ranking results are more reasonable, hence verifying the superiority of this model.

show abstract

“…To study real-time risks more accurately, Bi et al [19] used dynamic irregular grids to analyze and evaluate navigation safety. Li et al [20,21] and Guo et al [22] proposed using DBN to study risk evolution. Therefore, the introduction of the DBN method not only solved the uncertainty measurement problem based on risk information but also facilitated the analysis of risk characteristics in the spatial and temporal dimensions.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Pirate Attack Process Risk along the Maritime Silk Road via Dynamic Bayesian Network Analysis

Xia

Xuan

et al. 2023

JMSE

Self Cite

View full text Add to dashboard Cite

The Maritime Silk Road (MSR) is an important channel for maritime trade between China and other countries in the world. Maritime piracy has brought huge security risks to ships’ navigation and has seriously threatened the lives and property of crew members. To reduce the likelihood of attacks from pirates, it is necessary to study the risk to a ship exposed to attacks from pirates on the MSR. Firstly, risk factors were established from three risk component categories (hazard, mitigation capacity, and vulnerability and exposure) and the risk index system of piracy and armed robbery events was founded. Secondly, the dynamic Bayesian network (DBN) method was introduced to establish a pirate attack risk assessment model ad to conduct a quantitative analysis of the process risk of a ship being attacked by pirates. Finally, combined with the scene data of the MSR, the process risk of a ship being attacked by pirates was modeled and applied as an example. The results showed that the overall risk of a ship being attacked by pirates is the lowest in July and the highest in March. In the whole route, when the ship was in the Gulf of Guinea, the Gulf of Aden–Arabian Sea, and the Strait of Malacca, the risk of pirate attack was the highest. This dynamic network model can effectively analyze the level of risk of pirate attacks on ships, providing a reference for the safety decision-making of ships on ocean routes.

show abstract

Using DBN and evidence-based reasoning to develop a risk performance model to interfere ship navigation process safety in Arctic waters

Cited by 29 publications

References 38 publications

Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN

Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN

Risk Assessment Method for Ship Based on Improved Fuzzy Multicriteria Decision-Making

Exploring the Pirate Attack Process Risk along the Maritime Silk Road via Dynamic Bayesian Network Analysis

Contact Info

Product

Resources

About