A Classification Approach Using Machine Learning for Predicting Traffic Flows in Areas with Missing Sensors

Reference : A Classification Approach Using Machine Learning for Predicting Traffic Flows in Area...


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/54423

Title :	A Classification Approach Using Machine Learning for Predicting Traffic Flows in Areas with Missing Sensors
Language :	English
Author, co-author :	Fazio, Martina [> >]
	Vitello, Piergiorgio [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)]
	Pineda Jaramillo, Juan Diego [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)]
	Connors, Richard [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)]
	Viti, Francesco [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)]
Publication date :	2022
Main document title :	Transportation Research Board 101st Annual Meeting
Peer reviewed :	Yes
Event name :	TRB 2022
Event date :	January 2022
Permalink :	http://hdl.handle.net/10993/54423
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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	File	Commentary	Version	Size	Access
Open access	TRB_Fazio et al.pdf		Author preprint	1.53 MB	View/Open

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