Integrating Bayesian Network and Cloud Model to Probabilistic Risk Assessment of Maritime Collision Accidents in China’s Coastal Port Waters DOI Creative Commons
Zhuang Li,

Xiaoming Zhu,

Shiguan Liao

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(12), P. 2113 - 2113

Published: Nov. 21, 2024

Ship collision accidents have a greatly adverse impact on the development of shipping industry. Due to uncertainty relating these accidents, maritime risk is often difficult accurately quantify. This study innovatively proposes comprehensive method combining qualitative and quantitative methods predict ship accidents. First, in view uncertain factors, Bayesian network analysis was used characterize correlations between accident assessment model established. Secondly, information about subjective data quantification based cloud adopted, reasoning determined multi-source fusion. The proposed applied spatiotemporal China’s coastal port waters. results show that there higher Guangzhou Port Ningbo China, potential for southern China greater, occurrence most affected by environment operations operators. Combining integrating conduct an assessment, this innovative has significance improving prevention response risks navigation ports.

Language: Английский

Cause analysis and management strategies for ship accidents: A Bayesian decision support model DOI
Jie Xue,

Peijie Yang,

Ziheng Wang

et al.

Ocean Engineering, Journal Year: 2025, Volume and Issue: 320, P. 120291 - 120291

Published: Jan. 10, 2025

Language: Английский

Citations

1
Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases DOI Creative Commons
Shengkui Zeng,

You Qi-dong,

Jianbin Guo

et al.

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(1), P. 158 - 158

Published: Jan. 17, 2025

Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover human–autonomy interaction process (HAIP) still critical for safety. Whether humans take over relies on situation awareness (SA) about correctness of decisions, which distorted by anchoring omission bias. Specifically, (i) bias (tendency to confirm prior opinion) causes imperception key information miscomprehending decisions; (ii) (inaction tendency) overestimation predicted loss caused takeover. This paper proposes a novel HAIP safety assessment method considering effects above biases. First, an SA-based decision model (SAB-TDM) proposed. In SAB-TDM, SA perception comprehension affected are quantified with Adaptive Control Thought-Rational (ACT-R) theory Anchoring Adjustment Model (AAM); behavioral utility prediction Prospect Theory. Second, guided dynamic Bayesian network assess A case study autonomous ship collision avoidance verifies effectiveness method. Results show that biases mutually contribute seriously threaten

Language: Английский

Citations

1
Lifecycle Risk Assessment for Steel Cargo Vessel Sinkings: An Interpretive Structural Modeling and Fuzzy Bayesian Network Approach DOI Creative Commons
Xiaodan Jiang,

Xu Haibin,

Yongwen Zhu

et al.

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(1), P. 165 - 165

Published: Jan. 18, 2025

Steel cargo vessel sinking accidents (SCVSA) threaten maritime safety and disrupt global steel supply chains. This study integrates interpretive structural modeling (ISM) fuzzy Bayesian networks (FBN) to evaluate SCVSA risks across the incident lifecycle. ISM identifies hierarchical relationships among multifaceted risk factors. FBN assesses lifecycle using scoring, modular nodes, a structure, with muti-source data drawn from accident reports, expert opinions, research studies. Experts estimate probabilities based on observations causal scenarios involving vessels at Shanghai Port. The ISM–FBN framework visualizes factors incorporates uncertainty in through updates, probability learning. approach provides robust adaptable tool for assessing risks, advancing assessment methodologies. Key findings identify advanced age, severe weather sea conditions, inadequate regulatory oversight as primary root causes. Poor loading stowage practices are direct contributors. Intermediate deeper surface layers flow shipping companies crew further environmental conditions. Multi-stage include emergency responses improper securing. To mitigate these actionable insights provided, including fleet modernization, enhanced compliance, training, improved preparedness.

Language: Английский

Citations

1
Integration of MIMAH and Fuzzy Bayesian Networks for risk analysis in chemical tanker loading operations DOI
Cenk Ay

Journal of Marine Engineering & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: Feb. 13, 2025

This study provides a systematic risk assessment approach for chemical tanker loading operations, focusing on high-risk scenario identified through operational data from model vessel. To address the complexities of transportation, hybrid methodology combining Methodology Identification Major Accident Hazards (MIMAH) and Fuzzy Bayesian Network (FBN) analysis was developed. MIMAH's structured framework systematically identifies critical events using Bow-Tie (BT) diagram, integrating Fault Tree (FT) Event (ET) providing thorough breakdown potential accident pathways. BT structure converted into (BN) to improve probability estimations by incorporating conditional dependencies expert-driven fuzzy logic, particularly where historical limited. The further employed dual-method sensitivity analysis, Fussell-Vesely (FV) importance measures Improvement Index (II), identify improvement-prone basic (BEs). Key findings highlight dominance human error in events, manifold connection failures incorrect valve alongside mechanical vulnerabilities with significant improvement potential. extends ARAMIS principles maritime contexts, reliability-based fuzzy-based estimation methods detailed adaptable that enhances safety resilience hazardous transport.

Language: Английский

Citations

1
Virtual-Reality-generated-data-driven Bayesian networks for risk analysis DOI
Huixing Meng,

Shijun Zhao,

Wenjuan Song

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 111053 - 111053

Published: March 1, 2025

Language: Английский

Citations

1
Application of Digital Twin in Large-Scale Energy Equipment Based on Numerical Analysis Technology DOI
Yunfei Zhao,

Caifu Qian,

Zhiwei Wu

et al.

Environmental science and engineering, Journal Year: 2025, Volume and Issue: unknown, P. 223 - 236

Published: Jan. 1, 2025

Language: Английский

Citations

0
Comprehensive lifecycle safety risk assessment for construction robotics using T-S fault tree analysis and Bayesian network DOI
Liying Wang,

Yuecheng Huang,

Yao Wang

et al.

Automation in Construction, Journal Year: 2025, Volume and Issue: 172, P. 106041 - 106041

Published: Feb. 12, 2025

Language: Английский

Citations

0
Neural domains and game strategies in collision risk mapping in algorithms for safe control in multi-autonomous ship situations DOI

J.J. Lisowski

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

Published: April 14, 2025

Abstract As maritime transport technology has shifted towards the greater use of autonomous ships, safety requirements for their movement are growing. A gap in scope direct representation collision risk object control algorithm exists. In this study, intelligent methods engineering objects were developed to assess multi-object situations. These included crisis management before collisions determine optimal and safe ship trajectories. The value was determined from domains generated by neural network or its three appropriate mathematical models. basis these considerations dynamic game control. Simulations algorithms performed on examples real navigation situations under different environmental conditions enabled assessment effectiveness most effective good traffic algorithm, whereas noncooperative cooperative restricted objects. results study provide awareness that can improve navigation.

Language: Английский

Citations

0
A methodology to quantify risk evolution in typhoon-induced maritime accidents based on directed-weighted CN and improved RM DOI
Laihao Ma, Xiaoxue Ma,

Liguang Chen

et al.

Ocean Engineering, Journal Year: 2025, Volume and Issue: 319, P. 120303 - 120303

Published: Jan. 6, 2025

Language: Английский

Citations

0
A multi-source data-driven approach for navigation safety integrating computational intelligence and Bayesian networks DOI Creative Commons

Xiaotong Qu,

Chengbo Wang

Frontiers in Marine Science, Journal Year: 2025, Volume and Issue: 12

Published: Feb. 3, 2025

Ships often face various risks when sailing at sea, ranging from harsh natural environments to complex traffic conditions. To reduce the impact of these on ships and crews, this paper proposes a navigation risk assessment method that integrates computational intelligence (CI) techniques, such as fuzzy logic, with Bayesian networks (BNs) utility theory. Firstly, system is established using maritime data expert knowledge, which evaluates spatial perspective by considering factors safeguard accident conditions across different regions. Secondly, logic-based numerical transformation proposed derive prior probabilities in BNs. The weighted rule base used capture dependencies among factors. Finally, probability distribution determined combining dependencies, are converted into index values through Taking grid-based South China Sea an example, effectiveness verified. results study provide theoretical support for based multi-source reference formulate regulatory policies.

Language: Английский

Citations

0