Integrated satellite-terrestrial networks toward 6G: Architectures, applications, and challenges

X Zhu, C Jiang - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
With the increasing global communication demands and the development of Internet of
Things (IoT), extending the connectivity to rural and remote areas has become imperative for …

[HTML][HTML] Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review

Y Yang, Y Liu, G Li, Z Zhang, Y Liu - Transportation research part E …, 2024 - Elsevier
Abstract Automatic Identification System (AIS) data holds immense research value in the
maritime industry because of its massive scale and the ability to reveal the spatial–temporal …

Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime Internet of Things

RW Liu, M Liang, J Nie, WYB Lim… - … on Network Science …, 2022 - ieeexplore.ieee.org
The maritime Internet of Things (IoT) has recently emerged as a revolutionary
communication paradigm where a large number of moving vessels are closely …

A new method of inland water ship trajectory prediction based on long short-term memory network optimized by genetic algorithm

L Qian, Y Zheng, L Li, Y Ma, C Zhou, D Zhang - Applied Sciences, 2022 - mdpi.com
Ship position prediction plays a key role in the early warning and safety of inland waters and
maritime navigation. Ship pilots must have in-depth knowledge of the future position of their …

[HTML][HTML] Machine learning in beyond 5G/6G networks—State-of-the-art and future trends

VP Rekkas, S Sotiroudis, P Sarigiannidis, S Wan… - Electronics, 2021 - mdpi.com
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …

Fine-grained vessel traffic flow prediction with a spatio-temporal multigraph convolutional network

M Liang, RW Liu, Y Zhan, H Li, F Zhu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The accurate and robust prediction of vessel traffic flow is gaining importance in maritime
intelligent transportation system (ITS), such as vessel traffic services, maritime spatial …

Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery

H Li, JSL Lam, Z Yang, J Liu, RW Liu, M Liang… - … Research Part C …, 2022 - Elsevier
Owing to the space–air–ground integrated networks (SAGIN), seaborne ship** has
attracted increasing interest in the research on the motion behavior knowledge extraction …

[HTML][HTML] A machine learning method for the evaluation of ship grounding risk in real operational conditions

M Zhang, P Kujala, S Hirdaris - Reliability Engineering & System Safety, 2022 - Elsevier
Ship groundings may often lead to damages resulting in oil spills or ship flooding and
subsequent capsizing. Risks can be estimated qualitatively through experts' judgment or …

Sine-SSA-BP ship trajectory prediction based on chaotic map** improved sparrow search algorithm

Y Zheng, L Li, L Qian, B Cheng, W Hou, Y Zhuang - Sensors, 2023 - mdpi.com
Objective: In this paper, we propose a Sine chaos map**-based improved sparrow search
algorithm (SSA) to optimize the BP neural network for trajectory prediction of inland river …

[HTML][HTML] AISClean: AIS data-driven vessel trajectory reconstruction under uncertain conditions

M Liang, J Su, RW Liu, JSL Lam - Ocean Engineering, 2024 - Elsevier
In maritime transportation, intelligent vessel surveillance has become increasingly prevalent
and widespread by collecting and analyzing high massive spatial data from automatic …