Aproximación Bayesiana aplicada al Reparto Modal en Modelos de Transporte
- Beatriz González Pérez Directeur/trice
- Miguel Ángel Gómez Villegas Directeur
Université de défendre: Universidad Complutense de Madrid
Fecha de defensa: 28 janvier 2021
- Rosario Susi García President
- Isabel Salazar Mendoza Secrétaire
- Rosa Ríos Prado Rapporteur
- Juan Miguel Marín Díazaraque Rapporteur
- Manuel Mendoza Ramirez Rapporteur
Type: Thèses
Résumé
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...