A5000032674- Maritime Navigation and Safety
- Maritime Ports and Logistics
- Ship Hydrodynamics and Maneuverability
- Structural Integrity and Reliability Analysis
- Risk and Safety Analysis
- Maritime Transport Emissions and Efficiency
- Maritime Security and History
- Marine and Coastal Research
- Robotic Path Planning Algorithms
- Arctic and Antarctic ice dynamics
- Underwater Vehicles and Communication Systems
- Cruise Tourism Development and Management
- Fluid Dynamics Simulations and Interactions
- Oil Spill Detection and Mitigation
- Arctic and Russian Policy Studies
- Energy Efficient Wireless Sensor Networks
- Bayesian Modeling and Causal Inference
- Transportation Planning and Optimization
- Human-Automation Interaction and Safety
- Indoor and Outdoor Localization Technologies
- Multi-Criteria Decision Making
- EEG and Brain-Computer Interfaces
- Autonomous Vehicle Technology and Safety
- Traffic and Road Safety
- Evaluation Methods in Various Fields
Wuhan University of Technology
2014-2024
China Ocean Shipping (China)
2021-2023
National Institute of Transport
2023
Kunming Medical University
2017-2023
Sanya University
2022
University of Lisbon
2015-2019
Aalto University
2019
Advanced Lightweight Engineering (Netherlands)
2019
Sichuan Agricultural University
2017
China University of Petroleum, Beijing
2014
This paper presents a big data analytics method for the proactive mitigation of grounding risk. The model encompasses dynamics ship motion trajectories while accounting kinematic uncertainties in real operational conditions. approach combines K-means and DB-SCAN (Density-Based Spatial Clustering Applications with Noise) clustering methods Principal Component Analysis (PCA) to group environmental factors. A Multiple-Output Gaussian Process Regression (MOGPR) is consequently used predict...
This article develops a Bayesian belief network model for the prediction of accident consequences in Tianjin port. The study starts with statistical analysis historical data six years from 2008 to 2013. Then is constructed express dependencies between indicator variables and consequences. statistics expert knowledge are synthesized obtain probability distribution By sensitivity analysis, several that have influence on identified, including navigational area, ship type time day. results...
A Bayesian network–based risk analysis approach is proposed to analyse the factors influencing maritime transport accidents. Comparing with previous studies in relevant literature, it reveals new features including (1) primary data directly derived from accident records by two major databanks Marine Accident Investigation Branch and Transportation Safety Board of Canada 2012 2017, (2) rational classification respect each types accidents for effective prevention, (3) quantification extent...
Psychological factors have been a critical cause of human errors in sectors such as health and aviation. However, there is little relevant research the maritime industry, even though significantly contribute to shipping accidents. It becomes more worrisome given that seafarers are changing their roles onboard ships due growth automation techniques sector. This pioneers conceptual framework for assessing seafarer psychological using neurophysiological analysis. quantitatively enables factor...
Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of primary issues reduce such In this paper, a quantitative real-time multi-ship collision risk analysis avoidance decision-making model proposed. Firstly, system was established under overall requirements International Code for Collision Avoidance at Sea (COLREGs) good seamanship, based five influencing factors. Then, fuzzy logic method used...