Modelos de aprendizaje computacional para la predicci´on de siniestralidad vial en Bogotá D.C

Currently road accidents are a problem that negatively worsens the socioeconomic environment of any country or city, which is why all governments seek feasible solutions that allow them to reduce the risk of mortality and accidents. The solutions that many governments have implemented are based on t...

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Detalles Bibliográficos
Autor principal:	Castellanos Cardozo, Sebastian Rodrigo
Otros Autores:	Ramírez Idárraga, Juan Camilo
Formato:	Trabajo de grado (Pregrado y/o Especialización)
Lenguaje:	spa
Publicado:	Universidad Antonio Nariño 2023
Materias:	Aprendizaje automático Modelos de predicción Siniestralidad vial Redes neuronales Bosques aleatorios Machine learning Prediction models road accident rate Neural networks Random forests
Acceso en línea:	http://repositorio.uan.edu.co/handle/123456789/8949
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Descripción
Sumario:	Currently road accidents are a problem that negatively worsens the socioeconomic environment of any country or city, which is why all governments seek feasible solutions that allow them to reduce the risk of mortality and accidents. The solutions that many governments have implemented are based on the resolution of article 74/299 “Improvement of road safety”, proclaiming the Decade of Action for Road Safety 2021-2023, held at the United Nations General Assembly