[HTML][HTML] Ship trajectory prediction based on machine learning and deep learning: A systematic review and methods analysis
Ship trajectory prediction based on Automatic Identification System (AIS) data has attracted
increasing interest as it helps prevent collision accidents and eliminate potential …
increasing interest as it helps prevent collision accidents and eliminate potential …
Applications of machine learning methods in port operations–A systematic literature review
Ports are pivotal nodes in supply chain and transportation networks, in which most of the
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
[HTML][HTML] AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods
Maritime transport faces new safety challenges in an increasingly complex traffic
environment caused by large-scale and high-speed ships, particularly with the introduction …
environment caused by large-scale and high-speed ships, particularly with the introduction …
Physics-informed machine learning models for ship speed prediction
This paper proposes a novel physics-informed machine learning method to build grey-box
model (GBM) predicting ship speed for ocean crossing ships. In this method, the expected …
model (GBM) predicting ship speed for ocean crossing ships. In this method, the expected …
k-GCN-LSTM: A k-hop Graph Convolutional Network and Long–Short-Term Memory for ship speed prediction
Ship speed information plays an important role in the maritime intelligent transportation
system, and ship speed prediction has attracted extensive attention in maritime community …
system, and ship speed prediction has attracted extensive attention in maritime community …
[HTML][HTML] Deep learning-based ship speed prediction for intelligent maritime traffic management
Improving maritime operations planning and scheduling can play an important role in
enhancing the sector's performance and competitiveness. In this context, accurate ship …
enhancing the sector's performance and competitiveness. In this context, accurate ship …
[HTML][HTML] A data mining-then-predict method for proactive maritime traffic management by machine learning
Proactive traffic management is increasingly critical in maritime intelligent transportation
systems. Central to this is maritime traffic forecasting, which leverages specific structures …
systems. Central to this is maritime traffic forecasting, which leverages specific structures …
Liner ship** connectivity: A dynamic link between energy trade, green exchange and inclusive growth using advanced econometric modelling
Y **, H Li, Y Yu, US Ahmad - Ocean & Coastal Management, 2024 - Elsevier
The ocean economy is crucial in facilitating green exchanges and promoting inclusive
growth. Despite its significance, this domain needs more investigation, leading to diverse …
growth. Despite its significance, this domain needs more investigation, leading to diverse …
Predicting PM10 and PM2. 5 concentration in container ports: A deep learning approach
SY Park, SH Woo, C Lim - Transportation Research Part D: Transport and …, 2023 - Elsevier
This study aims at predicting the concentrations of particulate matter in container ports.
Meteorological data, terminal operation data, and data on PM2. 5 and PM10 and other air …
Meteorological data, terminal operation data, and data on PM2. 5 and PM10 and other air …
Near-optimal weather routing by using improved A* algorithm
With soaring oil prices worldwide, determining the most optimal routes for economical ship
operation has become an important issue. Optimizing ship routes is economically important …
operation has become an important issue. Optimizing ship routes is economically important …