Cargando…
Dynamic Maritime Traffic Pattern Recognition with Online Cleaning, Compression, Partition, and Clustering of AIS Data
Maritime traffic pattern recognition plays a major role in intelligent transportation services, ship monitoring, route planning, and other fields. Facilitated by the establishment of terrestrial networks and satellite constellations of the automatic identification system (AIS), large quantities of s...
Autores principales: | Zhang, Yuanqiang, Li, Weifeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414815/ https://www.ncbi.nlm.nih.gov/pubmed/36016066 http://dx.doi.org/10.3390/s22166307 |
Ejemplares similares
-
The Piraeus AIS dataset for large-scale maritime data analytics
por: Tritsarolis, Andreas, et al.
Publicado: (2022) -
A Quasi-Intelligent Maritime Route Extraction from AIS Data
por: Onyango, Shem Otoi, et al.
Publicado: (2022) -
Design and Experiment of Satellite-Terrestrial Integrated Gateway with Dynamic Traffic Steering Capabilities for Maritime Communication
por: Koo, Hyounhee, et al.
Publicado: (2023) -
Leveraging extreme scale analytics, AI and digital twins for maritime digitalization: the VesselAI architecture
por: Ilias, Loukas, et al.
Publicado: (2023) -
Maritime sector at verge of change: learning and competence needs in Finnish maritime cluster
por: Kilpi, Vesa, et al.
Publicado: (2021)