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) …
Survey of maps of dynamics for mobile robots
TP Kucner, M Magnusson, S Mghames… - … Journal of Robotics …, 2023 - journals.sagepub.com
Robotic mapping provides spatial information for autonomous agents. Depending on the
tasks they seek to enable, the maps created range from simple 2D representations of the …
tasks they seek to enable, the maps created range from simple 2D representations of the …
[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 …
An adaptive federated learning scheme with differential privacy preserving
X Wu, Y Zhang, M Shi, P Li, R Li, NN Xiong - Future Generation Computer …, 2022 - Elsevier
Driven by the upcoming development of the sixth-generation communication system (6G),
the distributed machine learning schemes represented by federated learning has shown …
the distributed machine learning schemes represented by federated learning has shown …
SG-PBFT: A secure and highly efficient distributed blockchain PBFT consensus algorithm for intelligent Internet of vehicles
As an application of Internet of Things (IoT) technology, the Internet of Vehicles (IoV) faces
two main security issues:(1) the central server of the IoV may not be powerful enough to …
two main security issues:(1) the central server of the IoV may not be powerful enough to …
[HTML][HTML] Incorporation of AIS data-based machine learning into unsupervised route planning for maritime autonomous surface ships
Abstract Maritime Autonomous Surface Ships (MASS) are deemed as the future of maritime
transport. Although showing attractiveness in terms of the solutions to emerging challenges …
transport. Although showing attractiveness in terms of the solutions to emerging challenges …
Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery
Owing to the space–air–ground integrated networks (SAGIN), seaborne shipping has
attracted increasing interest in the research on the motion behavior knowledge extraction …
attracted increasing interest in the research on the motion behavior knowledge extraction …
A novel MP-LSTM method for ship trajectory prediction based on AIS data
The accurate prediction of ship trajectory has great significance in maritime transportation.
Among all the prediction methods, multi-step prediction has received increasing attention …
Among all the prediction methods, multi-step prediction has received increasing attention …
Adaptively constrained dynamic time warping for time series classification and clustering
Time series classification and clustering are important for data mining research, which is
conducive to recognizing movement patterns, finding customary routes, and detecting …
conducive to recognizing movement patterns, finding customary routes, and detecting …
An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation
To achieve reliable mining results for massive vessel trajectories, one of the most important
challenges is how to efficiently compute the similarities between different vessel trajectories …
challenges is how to efficiently compute the similarities between different vessel trajectories …