Diseño de un Prototipo de Software Basado en Redes Neuronales Artificiales para Predecir el Nivel de Ocupación y Proximidad de Buses Duales de la Ruta D81 del SITP

Abstract

In this document will find the results of analysis and design of a software prototype based in artificial neuronal network model (ANN) multilayer, which pretend predict, optimized and decrease of wait time in accordance at users’ boarding habits one of the route (D81) of the massive transport system Transmilenio, this software prototype will develop for mobile devices through the computational implementation of neuronal network model that allow self-learning and predict the more suitable transport service for the route final user in different travel point, in addition to this also provided to the user useful information such as buses arrival time, occupation rate and travel recommendations, this through the graphic interface user interactive that allow the making decisions.