Aproximación Bayesiana aplicada al Reparto Modal en Modelos de Transporte

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

Defentsa unibertsitatea: Universidad Complutense de Madrid

Fecha de defensa: 2021(e)ko urtarrila-(a)k 28

Epaimahaia:
  1. Rosario Susi García Presidentea
  2. Isabel Salazar Mendoza Idazkaria
  3. Rosa Ríos Prado Kidea
  4. Juan Miguel Marín Díazaraque Kidea
  5. Manuel Mendoza Ramirez Kidea
Saila:
  1. Estadística e Investigación Operativa

Mota: Tesia

Laburpena

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...