In today's world of transportation, road accidents are one of the most common problems. The world health organization has released a list of the top ten causes of human death, sadly, traffic accidents are in ninth place. Even in the automobile industry, many inventories make and produce safety features however, traffic accidents are inevitable. In this paper, the machine learning concept is applied to predict the severity of the accident and analyze factors like the number of accidents by year, Number of accidents by state, Accidents on the day of the week, road accidents by state day and hours, accidents ratio between rural and urban areas, Age people involved in the accidents, most dangerous time to drive, with the help of current dataset. This will be effective in improving safety measures and reducing traffic accidents.


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    Titel :

    Predictive Analytics of Road Accidents Using Machine Learning


    Beteiligte:
    Kaliraja, C (Autor:in) / Chitradevi, D (Autor:in) / Rajan, Anju (Autor:in)


    Erscheinungsdatum :

    2022-04-28


    Format / Umfang :

    390089 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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