Multivariate hierarchical DBSCAN model for enhanced maritime data analytics-Reference-Cited by-同舟云学术

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Multivariate hierarchical DBSCAN model for enhanced maritime data analytics

Published:2024-03 Issue: Volume:150 Page:102282
ISSN:0169-023X
Container-title:Data & Knowledge Engineering
language:en
Short-container-title:Data & Knowledge Engineering

Author:

Newaliya Nitin^ORCID,Singh Yudhvir

Funder

National Oceanic and Atmospheric Administration

Publisher

Elsevier BV

Reference57 articles.

1. Madhavan, N.,. 2018. Maritime security–are we reaching a tipping point?. https://www.linkedin.com/pulse/maritime-security-we-reaching-tipping-point-nitin-madhavan?trk=portfolio_article-card_title (accessed 23 April 2023).

2. IBM, 2023. AI-Powered Automation - Mayflower Autonomous Ship. https://www.ibm.com/cloud/automation/mayflower-autonomous-ship (accessed 23 April 2023).

3. Data-driven methods for detection of abnormal ship behavior: progress and trends;Wang;Ocean Eng.,2023

4. FleetMon, 2023. AIS Spoofing. https://help.fleetmon.com/en/articles/4379768-ais-spoofing (accessed 23 April 2023).

5. Panbo, 2023. Invalid MMSI numbers, a real problem. https://panbo.com/invalid-mmsi-numbers-a-real-problem (accessed 23 April 2023).

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on the Optimization of Ship Trajectory Clustering Based on the OD–Hausdorff Distance;Journal of Marine Science and Engineering;2024-08-15

2. DBSCAN Speedup for Time-Serpentine Datasets;Applied Computer Systems;2024-06-01

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