Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Garcia Rodenas, Ricardo"'
Publikováno v:
J.A. Mart\'in-Baos, R. Garc\'ia-R\'odenas, L. Rodriguez-Benitez, M. Bierlaire (2025). Scalable kernel logistic regression with Nystr\"om approximation: Theoretical analysis and application to discrete choice modelling. Neurocomputing 617
The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity h
Externí odkaz:
http://arxiv.org/abs/2402.06763
Autor:
Bešinović, Nikola, García-Ródenas, Ricardo, López-García, María Luz, López-Gómez, Julio Alberto, Martín-Baos, José Ángel
The liberalisation of the European passenger railway markets through the European Directive EU 91/440/EEC states a new scenario where different Railway Undertakings compete with each other in a bidding process for time slots. The infrastructure resou
Externí odkaz:
http://arxiv.org/abs/2401.12073
Autor:
Martín-Baos, José Ángel, López-Gómez, Julio Alberto, Rodriguez-Benitez, Luis, Hillel, Tim, García-Ródenas, Ricardo
Publikováno v:
J.\'A. Mart\'in-Baos, J. Alberto L\'opez-G\'omez, L. Rodriguez-Benitez, T. Hillel, R. Garc\'ia-R\'odenas (2023) A prediction and behavioural analysis of machine learning methods for modelling travel mode choice, 156, 104318
The emergence of a variety of Machine Learning (ML) approaches for travel mode choice prediction poses an interesting question to transport modellers: which models should be used for which applications? The answer to this question goes beyond simple
Externí odkaz:
http://arxiv.org/abs/2301.04404
Publikováno v:
In Neurocomputing 7 February 2025 617
Publikováno v:
In Computers and Operations Research April 2024 164
Publikováno v:
In Transportation Research Procedia 2022 62:815-823
Autor:
García-García, José Carlos, García-Ródenas, Ricardo, López-Gómez, Julio Alberto, Martín-Baos, José Ángel
Publikováno v:
In Transportation Research Procedia 2022 62:374-382
Publikováno v:
In Transportation Research Procedia 2022 62:43-50
Publikováno v:
In Applied Soft Computing Journal January 2022 115
Publikováno v:
In Transportation Research Procedia 2021 58:61-68