Civil aviation safety is one of the crucial problems of the aviation industry. Air traffic management as a core part of civil aviation is facing massive pressure of safety operation. Accurately evaluating unsafe events rate is essential to improving air traffic safety. This paper proposed a grey-buffer operator-Markov chain method to forecast the civil aviation unsafe events rate. It combined the grey system and Markov chain. When predicting the civil aviation unsafe events rate, the actual data samples are few, discrete, and random fluctuation, which often causes more significant relative errors and worse accuracy using the traditional grey model. However, the average weakening buffer operator is an excellent method to process the raw data. According to the distribution of relative value, we can build the prediction model, combining with the characteristics of Markov forecast volatile data sequence. Finally, this method is applied to predict the unsafe events rate of civil aviation. The experimental result shows that this method not only reduces the relative error of predicted value but also improves the prediction precision of the model.


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    Titel :

    Forecast of Civil Aviation Unsafe Events Rate Using Grey-Buffer Operator-Markov Chain Method


    Beteiligte:
    Guo, Jiuxia (Autor:in) / Gao, Ziliang (Autor:in) / Wang, Yinhai (Autor:in)

    Kongress:

    International Conference on Transportation and Development 2020 ; 2020 ; Seattle, Washington (Conference Cancelled)



    Erscheinungsdatum :

    2020-08-31




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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