ROBIN: Rail mOBIlity simulatioN
The use of simulators is frequent in the study of complex systems. They replicate a real system and allow obtaining data from the simulated process as well as providing a …
e.-del-castillo-herrera
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A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
Traditionally, Random Utility Maximization (RUM) models have been widely applied to travel mode choice modelling. Currently, Machine Learning (ML) models are being applied as an …
jose-carlos-garcia-garcia
A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
In the last few years, the success of Machine Learning (ML) algorithms has led to the extension of their applications to areas such as transport planning. One of the main tasks …
jose-angel-martin-baos
Discrete choice modeling using Kernel Logistic Regression
The Kernel Logistic Regression is a popular technique in machine learning. In this work this technique is applied to the field of discrete choice modeling. This approach is …
jose-angel-martin-baos
A general approach to fuzzy community detection in social networks
The present work addresses the problem of community detection in social networks. Determination of the community structure permits to identify the organizational and functional …
alfonso-nino