Publicaciones en las que colabora con Enrique Castillo Ron (14)

2016

  1. A Markovian-Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors

    Computer-Aided Civil and Infrastructure Engineering, Vol. 31, Núm. 3, pp. 193-218

  2. Bayesian Networks-Based Probabilistic Safety Analysis for Railway Lines

    Computer-Aided Civil and Infrastructure Engineering, Vol. 31, Núm. 9, pp. 681-700

  3. Coherent and Compatible Statistical Models in Structural Analysis

    International Journal of Computational Methods

  4. Probabilistic safety analysis of high speed railway lines including human errors

    Civil-Comp Proceedings

2014

  1. A hierarchical optimization problem: Estimating traffic flow using Gamma random variables in a Bayesian context

    Computers and Operations Research, Vol. 41, Núm. 1, pp. 240-251

  2. Non-planar hole-generated networks and link flow observability based on link counters

    Transportation Research Part B: Methodological, Vol. 68, pp. 239-261

  3. On the Probabilistic and Physical Consistency of Traffic Random Variables and Models

    Computer-Aided Civil and Infrastructure Engineering, Vol. 29, Núm. 7, pp. 496-517

  4. On the physical and probabilistic consistency of some engineering random models

    Structural Safety, Vol. 51, pp. 1-12

  5. Two applications of statistics to traffic models

    Communications in Statistics - Theory and Methods

2013

  1. A model for continuous dynamic network loading problem with different overtaking class users

    Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 17, Núm. 4, pp. 328-350

  2. A multiclass user equilibrium model considering overtaking across classes

    IEEE Transactions on Intelligent Transportation Systems, Vol. 14, Núm. 2, pp. 928-942

  3. A percentile system optimization approach with and without path enumeration

    Computers and Operations Research, Vol. 40, Núm. 11, pp. 2711-2723

  4. Deriving the upper bound of the number of sensors required to know all link flows in a traffic network

    IEEE Transactions on Intelligent Transportation Systems, Vol. 14, Núm. 2, pp. 761-771