Publications
(2023).
A prediction and behavioural analysis of machine learning methods for modelling travel mode choice.
Transportation Research Part C: Emerging Technologies.
(2023).
Machine learning methods applied to transport demand modelling.
Universidad de Castilla-La Mancha.
(2022).
A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling.
Transportation Research Procedia.
(2022).
IoT based monitoring of air quality and traffic using regression analysis.
Applied Soft Computing.
(2021).
A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression.
Transportation Research Procedia.
(2021).
Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach.
Transportation Letters.
(2020).
A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs.
Computational Statistics and Data Analysis.
(2020).
Discrete choice modeling using Kernel Logistic Regression.
Transportation Research Procedia.
(2019).
A general approach to fuzzy community detection in social networks.
Proceedings - International Conference on Computer Communications and Networks, ICCCN.
