With the significant increase in the frequency of social traffic activities, traffic safety issues have gradually become the focus of social attention. This paper aims to deeply explore the principles and operating steps of the ARIMA model (autoregressive moving average model) in time series analysis, and evaluate the model’s effectiveness in predicting traffic accident data with specific examples. The results show that the ARIMA model performs well in predicting the number of traffic accidents. The error analysis between the predicted data and the actual data provides a basis for further research and verifies the potential application of this method in traffic safety assessment.


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    Titel :

    Research on Traffic Safety Accident Prediction Based on ARIMA


    Weitere Titelangaben:

    Advances in Engineering res


    Beteiligte:
    Chen, Gongfa (Herausgeber:in) / Guo, Baohua (Herausgeber:in) / Chen, Yan (Herausgeber:in) / Guo, Jingwei (Herausgeber:in) / Wei, Ziyi (Autor:in) / Wang, Kefeng (Autor:in) / Gao, Jinhai (Autor:in)

    Kongress:

    International Conference on Rail Transit and Transportation ; 2024 ; Jiaozuo, China October 10, 2024 - October 12, 2024



    Erscheinungsdatum :

    15.12.2024


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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