Our goal for this challenge is to build a solution to accurately predict the destination port and arrival times of a given vessel using Bayesian inference and ...
Jun 29, 2018 · Our goal for this challenge is to build a solution to accurately predict the destination port and arrival times of a given vessel using Bayesian ...
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In this paper, an AIS data-driven method- ology is proposed for the estimation of vessel ETA at ports.
We propose a Bayesian population variability-based method to estimate the distributions of accident rates.
Mar 15, 2024 · Abstract—This paper investigates the prediction of vessels' arrival time to the pilotage area using multi-data fusion and.
This study proposes a data-driven solution for accurately predicting vessel arrival times using ML/DL techniques.
An economic trend is taken as an objective function and the DI and CI values are explanatory variables. The prediction model is defined as a Bayesian network.
Oct 27, 2020 · This paper presents a generic Bayesian framework that utilizes stochastic models that can capture the influence of intent (viz., destination) on the object ...
Sep 13, 2016 · The average "velocity" of all his ships is the distance between London and New York divided by the average trip time between London and New York.
Recent studies in the assessment of risk in maritime trans- portation systems have used simulation-based probabilistic techniques.