A robust assessment of inland waterway collision risk based on AIS and visual data fusion DOI
Haifeng Ding, Jinxian Weng

Ocean Engineering, Journal Year: 2024, Volume and Issue: 307, P. 118242 - 118242

Published: May 23, 2024

Language: Английский

A partially observable multi-ship collision avoidance decision-making model based on deep reinforcement learning DOI
Kangjie Zheng, Xinyu Zhang, Chengbo Wang

et al.

Ocean & Coastal Management, Journal Year: 2023, Volume and Issue: 242, P. 106689 - 106689

Published: June 26, 2023

Language: Английский

Citations

22
Spatio-temporal multi-graph transformer network for joint prediction of multiple vessel trajectories DOI
Ryan Wen Liu,

Weixin Zheng,

Maohan Liang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 129, P. 107625 - 107625

Published: Nov. 30, 2023

Language: Английский

Citations

18
PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships DOI Creative Commons
Bowen Lin, Mao Zheng, Bing Han

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(2), P. 202 - 202

Published: Jan. 23, 2024

Ship course-keeping control is of great significance to both navigation efficiency and safety. Nevertheless, the complex navigational conditions, unknown time-varying environmental disturbances, dynamic characteristics ships pose difficulties for ship course-keeping. Thus, a PSO-based predictive PID-backstepping (P-PB) controller proposed in this paper realize efficient rapid ships. The takes ship’s target course, current yawing speed, as well motion parameters into consideration. In design controller, PID improved by introducing control. Then, combined with backstepping balance stability Subsequently, are optimized utilizing Particle Swarm Optimization (PSO), which can adaptively adjust value various scenarios, thus further increase its efficiency. Finally, validated carrying out simulation tests scenarios. results show that it improves error time-response specification 4.19% 9.71% on average, respectively, efficiently achieve under

Language: Английский

Citations

8
Artificial Intelligence and Machine Learning for Green Shipping: Navigating towards Sustainable Maritime Practices DOI Creative Commons
Hoang Phuong Nguyen,

Cao Thao Uyen Nguyen,

Thi Men Tran

et al.

JOIV International Journal on Informatics Visualization, Journal Year: 2024, Volume and Issue: 8(1), P. 1 - 1

Published: March 1, 2024

This paper aims to investigate the role that artificial intelligence (AI) plays in promoting sustainability marine industry. The report demonstrates potential of AI-driven technology improve vessel operations, decrease emissions, and promote environmental stewardship. is shown by detailed examination existing trends, problems, possibilities. Several vital studies highlight significance policy interventions encourage use intelligence. These include financial incentives, legal frameworks, programs increase capability. Throughout this work, importance driving efficiency, safety, emphasized. work also highlights urgent need for action address climate change degradation sector. industry can lessen its carbon footprint, pollution, ecosystem health if it shifts various alternative fuels, renewable energy sources, technologies powered At end an appeal made policymakers, stakeholders, providers, urging them prioritize investments research development create collaboration speed up transition a sector more sustainable resilient.

Language: Английский

Citations

8
A robust assessment of inland waterway collision risk based on AIS and visual data fusion DOI
Haifeng Ding, Jinxian Weng

Ocean Engineering, Journal Year: 2024, Volume and Issue: 307, P. 118242 - 118242

Published: May 23, 2024

Language: Английский

Citations

7