A data-driven prioritisation framework to mitigate maintenance impact on passengers during metro line operation

Abstract The application of artificial intelligence (AI) techniques may lead to significant improvements in different aspects of rail sector. Considering asset management and maintenance, AI can improve data analysis and asset status forecasting and decision-making processes, fostering predictive an...

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Bibliographic Details

Main Authors:	Alice Consilvio, Giulia Vignola, Paula López Arévalo, Federico Gallo, Marco Borinato, Carlo Crovetto
Format:	Artigo
Language:	Inglês
Published:	SpringerOpen 2024-01-01
Series:	European Transport Research Review
Subjects:	Rail maintenance Service-based asset management systems Maintenance decision support User-oriented planning approach Passenger flow analysis Dynamic asset criticality
Online Access:	https://doi.org/10.1186/s12544-023-00631-z
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