Enhancing Prediction Accuracy of Vessel Arrival Times Using Machine Learning

Enhancing Prediction Accuracy of Vessel Arrival Times Using Machine Learning

Marine transportation accounts for approximately 90% of the total trade managed in international logistics and plays a vital role in many companies’ supply chains. However, en-route factors like weather conditions or piracy incidents often delay scheduled arrivals at destination ports, leading to do...

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Bibliographic Details
Main Authors: Nicos Evmides, Sheraz Aslam, Tzioyntmprian T. Ramez, Michalis P. Michaelides, Herodotos Herodotou
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Journal of Marine Science and Engineering
Subjects:
port terminals
machine learning
expected time of arrival (ETA) prediction
intelligent sea transportation
port efficiency
Online Access:https://www.mdpi.com/2077-1312/12/8/1362

Internet

https://www.mdpi.com/2077-1312/12/8/1362

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