This paper addresses the time slot allocation problem within the context of a liberalized passenger railway market as a multi-objective model. We propose two criteria for making …
In deregulated railway markets, efficient management of infrastructure charges is essential for sustaining railway systems. This study sets out a method for infrastructure managers …
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 …
This paper presents a software package developed in Python that allows the application of the technique known as Kernel Logistic Regression (KLR), a Machine Learning (ML) tool, to …
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 …