XGBoost in Public Transportation for Multi-Attribute Data: Delay Prediction in Railway Systems in Real-Time

XGBoost in Public Transportation for Multi-Attribute Data: Delay Prediction in Railway Systems in Real-Time

Predicting delays in metro and tram services is a complex task that requires advanced approaches, such as powerful machine learning tools. This study addresses this topic by applying the XGBoost and Bayesian Optimization (BO) algorithms, which offer a prediction horizon of 15 minutes instead of the...

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Bibliographic Details
Main Authors: Sondoss Chtioui, Sebti Mouelhi, Sebastien Saudrais, Toufik Azib, Marc Ille, Melanie Morel, Frederic Oru
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Urban rail systems
train departure delay prediction
extreme gradient boosting machine
Bayesian optimization
operational control center
planned timetable
Online Access:https://ieeexplore.ieee.org/document/10683692/

Internet

https://ieeexplore.ieee.org/document/10683692/

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