The Risk Analysis of Cart Development Based on Dynamic Bayesian Networks DOI Creative Commons
Junjun Liu, Jun Yu

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Abstract To address the issues of multiple uncertainties, complex structures, and unpredictability during development trolley, this paper proposes a risk analysis method for trolley based on dynamic Bayesian networks. First, extensive relevant literature applying rough set reduction theory optimization, factor checklist with 5 primary indicators 16 secondary is constructed. Next, network model established by introducing time dimension. Fuzzy expert scoring are used to quantify probabilities nodes, Leaky Noisy-or Gate expansion applied correct conditional probabilities. Finally, performed using bidirectional inference function network. The time-series variation curve obtained through case analysis. By reverse reasoning, key factors occurrence identified, corresponding response strategies proposed. research results provide new approach analyzing effectively controlling risks associated development.

Language: Английский

Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model DOI
Hong Wang, Ning Chen, Bing Wu

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 249, P. 110201 - 110201

Published: May 14, 2024

Language: Английский

Citations

24
Incorporation of a global perspective into data-driven analysis of maritime collision accident risk DOI Creative Commons
Huanhuan Li, Cihad Çelik, Musa Bashir

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 249, P. 110187 - 110187

Published: May 15, 2024

Ship collision accidents are one of the most frequent accident types in global maritime transportation. Nevertheless, conducting an in-depth analysis prevention poses a formidable challenge due to constraints limited Risk Influential Factors (RIFs) and available datasets. This paper aims incorporate perspective into new data-driven risk model, scrutinize root causes accidents, advance measures for their mitigation. Additionally, it seeks analyze spatial distribution conduct comprehensive comparative study on characteristics both pre- post-COVID-19, utilizing real dataset collected from two reputable organizations: Global Integrated Shipping Information System (GISIS) Lloyd's Register Fairplay (LRF). The research findings implications encompass several crucial aspects: 1) constructed model demonstrates its reliability accuracy predicting as evident prediction performance various scenario analysis; 2) hazardous voyage segment is identified provide valuable guidance different stakeholders; 3) hierarchical significance ship context highlighted regarding probable occurrences; 4) During pandemic, rise probabilities, particularly involving older vessels bulk carriers, implies heightened operational challenges or maintenance issues these types; (5) prominence favorable adverse sea conditions reports underscores significant influence weather during pandemic. These help enhance safety protocols, ultimately reducing frequency domain.

Language: Английский

Citations

23
Navigating uncertainty: A dynamic Bayesian network-based risk assessment framework for maritime trade routes DOI
Hanwen Fan,

Haiying Jia,

Xuzhuo He

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 250, P. 110311 - 110311

Published: July 1, 2024

Language: Английский

Citations

18
Investigation of ship collision accident risk factors using BP-DEMATEL method based on HFACS-SCA DOI
Mingyang Guo, Miao Chen, Lihao Yuan

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: 257, P. 110875 - 110875

Published: Jan. 31, 2025

Language: Английский

Citations

5
Development of An Improved Bayesian Network Method for Maritime Accident Safety Assessment Based on Multiscale Scenario Analysis Theory DOI
Dewei Kong,

Zelong Lin,

Wei Li

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 251, P. 110344 - 110344

Published: July 11, 2024

Language: Английский

Citations

17
Research on scenario deduction and emergency decision-making evaluation for construction safety accidents DOI
Jianjun She, Zihao Guo, Zhijian Li

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 251, P. 110317 - 110317

Published: Nov. 1, 2024

Language: Английский

Citations

15
Application of bayesian network in the maritime industry: Comprehensive literature review DOI
Isaac Animah

Ocean Engineering, Journal Year: 2024, Volume and Issue: 302, P. 117610 - 117610

Published: March 28, 2024

Language: Английский

Citations

13
A novel hybrid deep-learning framework for medium-term container throughput forecasting: an application to China’s Guangzhou, Qingdao and Shanghai hub ports DOI
Di Zhang,

Xinyuan Li,

Chengpeng Wan

et al.

Maritime Economics & Logistics, Journal Year: 2024, Volume and Issue: 26(1), P. 44 - 73

Published: Feb. 16, 2024

Language: Английский

Citations

12
Structure model-based hazard identification method for autonomous ships DOI Creative Commons
Megumi Shiokari, Hiroko Itoh,

Tomohiro Yuzui

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 247, P. 110046 - 110046

Published: Feb. 29, 2024

There is great interest in the practical use of autonomous ships. Although it important to identify and address serious hazards at initial design stage when constructing complicated large-scale systems, difficult capture entire structure such a system. To this issue, study, we propose model–based hazard identification (SMB-HAZID) method, which suitable for performing The primary feature method using task (ST) diagrams, checklist, keywords. includes modeling that can describe overall system together with each component's tasks, information necessary execution, interactions among components an ST diagram. In addition, paper presents example perform hypothetical ship early stage. Through trial application, confirmed SMB-HAZID analyzing within ship. our future research, will improve proposed by developing incorporating technique quantifying or semi-quantifying risks corresponding identified hazards.

Language: Английский

Citations

12
Operational resilience modeling of cross-border freight railway systems: A study of strategies to improve proactive and reactive capabilities DOI
Haiwen Li, Lin Qi, Mudan Wang

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 110856 - 110856

Published: Jan. 1, 2025

Language: Английский

Citations

2