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Integrated satellite-terrestrial networks toward 6G: Architectures, applications, and challenges
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 …
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
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 …
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
The maritime Internet of Things (IoT) has recently emerged as a revolutionary
communication paradigm where a large number of moving vessels are closely …
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 …
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
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 …
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
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 …
intelligent transportation system (ITS), such as vessel traffic services, maritime spatial …
Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery
Owing to the space–air–ground integrated networks (SAGIN), seaborne ship** 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 …
[HTML][HTML] A machine learning method for the evaluation of ship grounding risk in real operational conditions
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 …
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 …
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
In maritime transportation, intelligent vessel surveillance has become increasingly prevalent
and widespread by collecting and analyzing high massive spatial data from automatic …
and widespread by collecting and analyzing high massive spatial data from automatic …