Accidents pose significant obstacles to economic progress and quality of life, especially in developing countries. Thailand faces such challenges and this research seeks to assess the frequency and most common causes of road accidents that lead to fatalities. This study employed the Apriori algorithm to examine the interrelationships among factors contributing to accidents in order to inform policymaking for reducing accident rates, minimizing economic and human losses, and enhancing the effectiveness of the healthcare system. By analyzing road accident data from 2015 to 2020 in Thailand (167,820 accidents causing THB 1.13 billion in damages), this article specifically focuses on the drivers responsible for fatal highway accidents. The findings reveal several interconnected variables that heighten the likelihood of fatalities, such as male gender, exceeding speed limits, riding a motorbike, traveling on straight roads, encountering dry surface conditions, and clear weather. An association rule analysis underscores the increased risk of injury or death in traffic accidents.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Application of the Apriori Algorithm for Traffic Crash Analysis in Thailand


    Beteiligte:


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Discovering Insightful Rules among Truck Crash Characteristics using Apriori Algorithm

    Jungyeol Hong / Reuben Tamakloe / Dongjoo Park | DOAJ | 2020

    Freier Zugriff


    Application of Apriori Algorithm in the Lamination Process in Yacht Production

    Niksa-Rynkiewicz, Tacjana / Landowski, Michal / Szalewski, Paweł | Online Contents | 2020


    Application of Apriori Algorithm in the Lamination Process in Yacht Production

    Niksa-Rynkiewicz Tacjana / Landowski Michal / Szalewski Paweł | DOAJ | 2020

    Freier Zugriff