A method for recognizing multi-dimensional anomalous urban traffic events based on a ternary Gaussian mixture model includes: reading a data sample of urban road traffic events; randomly dividing the data sample into a first subsample and a second subsample; performing modeling based on the first subsample by using the ternary Gaussian mixture model to obtain a second ternary Gaussian mixture model to calculate a distribution probability p of any sample point; clustering the second subsample, recognizing an outlier in the second subsample, and labeling the outlier and a normal point to obtain a labeled subsample; calculating the labeled subsample to obtain the distribution probability p corresponding to each sample point in the labeled subsample; when a new traffic event occurs, obtaining features of three dimensions of the new traffic event, calculating a distribution probability p by using the second model, and recognizing the new traffic event as anomalous if p


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    Title :

    Method for recognizing multi-dimensional anomalous urban traffic event based on ternary gaussian mixture model


    Contributors:
    WU CHAOTENG (author) / ZHANG LU (author) / GAO XIAO (author) / ZHOU YU (author) / ZHAO WEI (author) / YANG XUECHEN (author)

    Publication date :

    2022-04-12


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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