Aproximación Bayesiana aplicada al Reparto Modal en Modelos de Transporte

  1. de Gregorio Vicente, Oscar
Dirigida per:
  1. Beatriz González Pérez Director/a
  2. Miguel Ángel Gómez Villegas Director

Universitat de defensa: Universidad Complutense de Madrid

Fecha de defensa: 28 de de gener de 2021

Tribunal:
  1. Rosario Susi García Presidenta
  2. Isabel Salazar Mendoza Secretària
  3. Rosa Ríos Prado Vocal
  4. Juan Miguel Marín Díazaraque Vocal
  5. Manuel Mendoza Ramirez Vocal
Departament:
  1. Estadística e Investigación Operativa

Tipus: Tesi

Resum

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...