Real-Time Passenger Train Delay Prediction Using Machine Learning: A Case Study With Amtrak Passenger Train Routes

Real-Time Passenger Train Delay Prediction Using Machine Learning: A Case Study With Amtrak Passenger Train Routes

Passenger train delay significantly influences riders’ decision to choose rail transport as their mode choice. This article proposes real-time passenger train delay prediction (PTDP) models using the following machine learning techniques: random forest (RF), gradient boosting machine (GBM...

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Bibliographic Details
Main Authors: Pipatphon Lapamonpinyo, Sybil Derrible, Francesco Corman
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
Subjects:
Big data
data science
gradient-boosting
machine learning
multi-layer perceptron
neural network
Online Access:https://ieeexplore.ieee.org/document/9846898/

Internet

https://ieeexplore.ieee.org/document/9846898/

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