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Title: Predicción de la gravedad de los heridos en accidentes de tráfico en Barcelona
Author: Vila Giménez, David
Director: Casas Roma, Jordi
Tutor: Parada Medina, Raúl
Keywords: smart city
predictive analytics
accident severity
Issue Date: Jan-2020
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Can we really prevent a traffic accident? and, consequently, is it in our hands to avoid the derived victims? The answer to these questions is complex since accidents are surrounded by a large (practically infinite) number of independent and, at first glance, random variables. For years, researchers have focused on using data mining techniques to draw conclusions about the causes of traffic accidents and thus apply future preventive measures. Of the many possible studies in this area, current work will focus on derived victims. It is intended to generate prediction models that allow predicting the severity of the people involved in an accident. For this, the area of the city of Barcelona will be studied and, based on different factors, models of logistic regression and random forest will be generated, which will categorize the severity of the victims.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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