Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Li, Yan; Li, Huanhuan; Zhang, Chao; Zhao, Yunfeng; Yang, Zaili

doi:10.1016/j.trc.2024.104648

Transportation Research Part C: Emerging Technologies

2024

DOI: 10.1016/j.trc.2024.104648

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Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Yan Li,

Huanhuan Li,

Chao Zhang

et al.

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Cited by 5 publications

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Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Cited by 5 publications

References 70 publications

Geohash coding-powered deep learning network for vessel trajectory prediction using clustered AIS data in maritime Internet of Things industries

Geohash coding-powered deep learning network for vessel trajectory prediction using clustered AIS data in maritime Internet of Things industries

Maritime traffic partitioning: An adaptive semi-supervised spectral regularization approach for leveraging multi-graph evolutionary traffic interactions

A novel method for ship carbon emissions prediction under the influence of emergency events

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