Article (Scientific journals)
Predicting the traction power of metropolitan railway lines using different machine learning models
Pineda Jaramillo, Juan Diego; Martinez-Fernandez, P.; Villalba-Sanchis, I. et al.
2021In International Journal of Rail Transportation, p. 461--478
Peer reviewed
 

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Disciplines :
Computer science
Author, co-author :
Pineda Jaramillo, Juan Diego ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Martinez-Fernandez, P.
Villalba-Sanchis, I.
Salvador-Zuriaga, P.
Insa-Franco, R.
External co-authors :
yes
Language :
English
Title :
Predicting the traction power of metropolitan railway lines using different machine learning models
Publication date :
2021
Journal title :
International Journal of Rail Transportation
Publisher :
Taylor Francis
Pages :
461--478
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 18 January 2023

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