Predicting the traction power of metropolitan railway lines using different machine learning models

PINEDA JARAMILLO, Juan Diego; Martinez-Fernandez, P.; Villalba-Sanchis, I.; Salvador-Zuriaga, P.; Insa-Franco, R.

doi:10.1080/23248378.2020.1829513

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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.

2021 • In International Journal of Rail Transportation, p. 461--478

Peer reviewed

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https://hdl.handle.net/10993/53928

DOI
10.1080/23248378.2020.1829513

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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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