Variable taxi-out time prediction based on machine learning with interpretable attributes

Variable taxi-out time prediction based on machine learning with interpretable attributes

This paper presents a machine learning-based approach for predicting the taxi-out time, with the departure process decomposed into two components: the time taken to travel from the gate to the departure queue, and the time spent in the departure queue. Gradient-Boosted Decision Tree (GBDT) models ar...

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Bibliographic Details
Main Authors: Lim, Yixiang, Alam, Sameer, Tan, Fengji, Lilith, Nimrod
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2024
Subjects:
Engineering
Variable Taxi Time
Machine Learning
Online Access:https://hdl.handle.net/10356/178975

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