Mixed Discrete-Continuous Railway Disruption-Length Models with Copulas

The uncertainty of railway disruption length hinders the performance of the Operational Control Centre Rail (OCCR) in Utrecht. One way to model this uncertainty is by representing the disruption length as a probabilistic distribution. A dependence model, taking the form of a joint distribution, between the disruption length and several...

The Copula Bayesian Network with mixed discrete and continuous nodes to forecast railway disruption lengths

The highly uncertain nature of a railway disruption complicates the tasks carried by the Dutch Operational Control Centre Rail (OCCR) in the Netherlands. A good prediction of disruption length is believed to help the decision making in dealing with the disruption. Zilko, et al. [Non-Parametric Bayesian Network to Forecast Railway Disruption...