Development Of A Predictive Model Of Automobile Accidents In The City Of Bogotá, Colombia.

The importance of information analysis has allowed great advances in recent years, including predictive analysis, which, based on a series of data, look for patterns to forecast unknown data. For this article, one of the algorithms for predictions within Machine Learning is used, such as Random Fore...

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Publicado en:Journal of Namibian Studies Vol. 33; pp. 2236 - 2251
Autores principales: H., Fredys A. Simanca, Blanco Garrido, Fabian, Barbosa Guerrero, Lugo Manuel, Abuchar Porras, Alexandra, Rozo, Jairo Jamith Palacios
Formato: Artículo
Publicado: Society of Cultural Studies & Social Sciences 2023 Special Issue
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          H., Fredys A. Simanca
          Blanco Garrido, Fabian
          Barbosa Guerrero, Lugo Manuel
          Abuchar Porras, Alexandra
          Rozo, Jairo Jamith Palacios
        affil:
          Profesor Investigador, Universidad Cooperativa de Colombia, Bogotá - Colombia
          Docente de Planta, Colegio Mayor de Cundinamarca, Bogotá - Colombia
          Docente de Planta, Universidad Distrital Francisco José de Caldas, Bogotá - Colombia
      su:
        Traffic accidents
        Model cars (Toys)
        Prediction models
        Python programming language
        Random forest algorithms
        Bogotá (Colombia)
      sug:
        subj:
          Bogotá (Colombia)
          Traffic accidents
          Model cars (Toys)
          Prediction models
          Python programming language
          Random forest algorithms
      keyword:
        accident prediction
        Accidents
        Random Forest
      ab: The importance of information analysis has allowed great advances in recent years, including predictive analysis, which, based on a series of data, look for patterns to forecast unknown data. For this article, one of the algorithms for predictions within Machine Learning is used, such as Random Forest. And, the algorithm is made in the Python programming language, in order to obtain the possible causes of accidents in the city of Bogotá. This information is taken from the open data of accidents registered in the city in order to know how many accidents will exist each day and what will be the causes to be analyzed and thus, find a concrete solution to these problems of accident rate with the purpose of reducing them considerably. In conclusion, results were obtained from the development of the algorithm that allow to predict with a certain degree of accuracy the automobile accident rate in the city.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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