Please use this identifier to cite or link to this item: https://dspace.univ-adrar.edu.dz/jspui/handle/123456789/7846
Title: Implementation of an application mobile for the traffic prediction
Authors: MOULAY, Hicham
GHAITAOUI, Moulay Elhadj
KABOU, Salheddine / supervisor
Keywords: Intelligent Systems
Ntelligence Artificielle
Réseaux De neurones
Système De Position
Estimation Du Temps De Trajet
Système De Transport Intelligent
nement Global
Apprentissage Automatique
Flux De trafic
Embouteillage
Apprentissage En Pro
Intelligence Artificielle - Flux de trafic - Embouteillage - Apprentissage en profondeur - Réseaux de neurones - Système de positionnement global - Système de transport intelligent - estimation du temps de trajet – Apprentissage automatique
Issue Date: 2022
Abstract: In this theis, we proposed a new deep learning model to predict travel time based on GPS data collected in the city of Adrar. Our approach is based on two essential parts: The first part focuses on the data collection. In this phase, an android application, called GPS Adrar, is developed for the purpose of collecting GPS coordinates from Adrar’s citizens. The second part concerns data processing. In this phase, all the data collected in the first part must be analyzed using a depp learning model. Next, the new model is integrated with an android application, called Wassalni that offers the user a better prediction of road traffic among a set of available destinations. The experimental results show that the proposed model offers high accuracy than Google Maps in most of the routes.
Description: Option: Intelligent Systems
URI: https://dspace.univ-adrar.edu.dz/jspui/handle/123456789/7846
Appears in Collections:Mémoires de Master

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