Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

S Kabir, Y Papadopoulos - Safety science, 2019‏ - Elsevier
Abstract System safety, reliability and risk analysis are important tasks that are performed
throughout the system life-cycle to ensure the dependability of safety-critical systems …

Review of techniques and challenges of human and organizational factors analysis in maritime transportation

B Wu, TL Yip, X Yan, CG Soares - Reliability Engineering & System Safety, 2022‏ - Elsevier
This paper summarises the advanced techniques adopted for the analysis of human and
organizational factors, which are the predominant factors in maritime accidents, and the …

[HTML][HTML] Data-driven Bayesian network for risk analysis of global maritime accidents

H Li, X Ren, Z Yang - Reliability Engineering & System Safety, 2023‏ - Elsevier
Maritime risk research often suffers from insufficient data for accurate prediction and
analysis. This paper aims to conduct a new risk analysis by incorporating the latest maritime …

[HTML][HTML] A big data analytics method for the evaluation of ship-ship collision risk reflecting hydrometeorological conditions

M Zhang, J Montewka, T Manderbacka, P Kujala… - Reliability Engineering & …, 2021‏ - Elsevier
This paper presents a big data analytics method for the evaluation of ship-ship collision risk
in real operational conditions. The approach makes use of big data from Automatic …

A predictive analytics method for maritime traffic flow complexity estimation in inland waterways

M Zhang, D Zhang, S Fu, P Kujala, S Hirdaris - Reliability Engineering & …, 2022‏ - Elsevier
Maritime traffic flow complexity is the factor that presents in most existing maritime safety
analysis methods. It is considered as one of the main influencing factors affecting maritime …

Analysis of factors affecting the severity of marine accidents using a data-driven Bayesian network

Y Cao, X Wang, Y Wang, S Fan, H Wang, Z Yang… - Ocean …, 2023‏ - Elsevier
A data-driven Bayesian network model (BN) is used to analyse the relationship between the
severity of marine accidents and relevant Accident Influential Factors (AIFs). Firstly, based …

Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network

S Fan, E Blanco-Davis, Z Yang, J Zhang… - Reliability Engineering & …, 2020‏ - Elsevier
A data-driven Bayesian network (BN) is used to investigate the effect of human factors on
maritime safety through maritime accident analysis. Its novelties consist of (1) manual …

A systematic analysis for maritime accidents causation in Chinese coastal waters using machine learning approaches

K Liu, Q Yu, Z Yuan, Z Yang, Y Shu - Ocean & Coastal Management, 2021‏ - Elsevier
Maritime safety is critical as many maritime accidents involve catastrophic consequences,
including both fatalities and financial loss. To identify the factors which caused maritime …

Analyzing barriers to inland waterways as a sustainable transportation mode in India: A dematel-ISM based approach

A Trivedi, SK Jakhar, D Sinha - Journal of Cleaner Production, 2021‏ - Elsevier
Finding sustainable measures for maritime transport has long been a significant issue owing
to a rising global population and the internationalization of supply chains. In Indian contexts …

Bayesian network modeling of accident investigation reports for aviation safety assessment

X Zhang, S Mahadevan - Reliability Engineering & System Safety, 2021‏ - Elsevier
Safety assurance is of paramount importance in the air transportation system. In this paper,
we analyze the historical passenger airline accidents that happened from 1982 to 2006 as …