Aproximación Bayesiana aplicada al Reparto Modal en Modelos de Transporte

  1. de Gregorio Vicente, Oscar
Dirixida por:
  1. Beatriz González Pérez Director
  2. Miguel Ángel Gómez Villegas Director

Universidade de defensa: Universidad Complutense de Madrid

Fecha de defensa: 28 de xaneiro de 2021

Tribunal:
  1. Rosario Susi García Presidente/a
  2. Isabel Salazar Mendoza Secretario/a
  3. Rosa Ríos Prado Vogal
  4. Juan Miguel Marín Díazaraque Vogal
  5. Manuel Mendoza Ramirez Vogal

Tipo: Tese

Teseo: 155177 DIALNET lock_openDocta Complutense editor

Resumo

The work showed in this Report is aimed at demonstrating that the use of Bayesian Networks (RB), applied to the area of transport planning, represents an innovative improvement compared to other techniques commonly used to date such as Logit models and Neural Networks (RN). Specifically, its use in the stage of modal split of four-stage demand models (trip generation, distribution, modal split and assignment), which is the one in which the decision unit is faced within a discreet set of alternatives, both for passengers and freight...