A survey on deep learning for human mobility
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …
such as disease spreading, urban planning, well-being, pollution, and more. The …
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 …
Data-driven trajectory quality improvement for promoting intelligent vessel traffic services in 6G-enabled maritime IoT systems
Future generation communication systems, such as 5G and 6G wireless systems, exploit the
combined satellite-terrestrial communication infrastructures to extend network coverage and …
combined satellite-terrestrial communication infrastructures to extend network coverage and …
The application of artificial intelligence technology in shipping: A bibliometric review
Artificial intelligence (AI) technologies are increasingly being applied to the shipping
industry to advance its development. In this study, 476 articles published in the Science …
industry to advance its development. In this study, 476 articles published in the Science …
Anomaly detection in maritime AIS tracks: A review of recent approaches
The automatic identification system (AIS) was introduced in the maritime domain to increase
the safety of sea traffic. AIS messages are transmitted as broadcasts to nearby ships and …
the safety of sea traffic. AIS messages are transmitted as broadcasts to nearby ships and …
Maritime traffic probabilistic prediction based on ship motion pattern extraction
This paper proposes a novel maritime traffic prediction method based on ship motion pattern
extraction, considering ship destination prediction and ship trajectory prediction within a …
extraction, considering ship destination prediction and ship trajectory prediction within a …
[HTML][HTML] Ship trajectory prediction based on bi-LSTM using spectral-clustered AIS data
J Park, J Jeong, Y Park - Journal of marine science and engineering, 2021 - mdpi.com
According to the statistics of maritime accidents, most collision accidents have been caused
by human factors. In an encounter situation, the prediction of ship's trajectory is a good way …
by human factors. In an encounter situation, the prediction of ship's trajectory is a good way …
A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis
Identifying and assessing the likelihood and consequences of maritime accidents has been
a key focus of research within the maritime industry. However, conventional methods utilised …
a key focus of research within the maritime industry. However, conventional methods utilised …
Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis
W Zhang, X Feng, F Goerlandt, Q Liu - Reliability Engineering & System …, 2020 - Elsevier
Estimating the navigational risk of vessels operating in sea and waterway areas is important
for waterway risk management and pollution preparedness and response planning. Existing …
for waterway risk management and pollution preparedness and response planning. Existing …
Data-driven methods for detection of abnormal ship behavior: Progress and trends
Maritime traffic safety influences the development of world economies. A major aspect to
enhance maritime traffic safety is the effective detection of abnormal ship behavior (DASB) …
enhance maritime traffic safety is the effective detection of abnormal ship behavior (DASB) …