The invention discloses a traffic time series data anomaly detection method fusing multiple mechanisms, and relates to the technical field of data anomaly detection. Acquiring traffic time sequence data of a previous time period of the to-be-predicted time period; taking the traffic time sequence data of the previous time period as the input of a traffic time sequence data prediction model for operation, and obtaining the traffic time sequence prediction data of the to-be-predicted time period; determining a Gaussian distribution probability density value of a traffic data error value corresponding to each time point of the to-be-predicted time period based on the traffic data error value corresponding to the same time point in the traffic time sequence data of the to-be-predicted time period and the traffic time sequence prediction data of the to-be-predicted time period; and determining whether the traffic data corresponding to each time point in the traffic time sequence data of the to-be-predicted time period is abnormal or not based on the Gaussian distribution probability density value. According to the traffic time series data anomaly detection method fusing multiple mechanisms disclosed by the invention, anomaly detection can be accurately carried out on long-sequence traffic time series data.

    本发明公开了一种融合多种机制的交通时序数据异常检测方法,涉及数据异常检测技术领域。获取待预测时段的上一时段的交通时序数据;将上一时段的交通时序数据,作为交通时序数据预测模型的输入进行运算,得到待预测时段的交通时序预测数据;基于待预测时段的交通时序数据与待预测时段的交通时序预测数据中,同一时间点所对应的交通数据误差值,确定出待预测时段的各时间点所对应交通数据误差值的高斯分布概率密度值;基于高斯分布概率密度值,确定出待预测时段的交通时序数据中各时间点所对应的交通数据是否存在异常。本发明公开的融合多种机制的交通时序数据异常检测方法能够准确地对长序列的交通时序数据进行异常检测。


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    Title :

    Traffic time series data anomaly detection method fusing multiple mechanisms


    Additional title:

    一种融合多种机制的交通时序数据异常检测方法


    Contributors:
    LI YUFENG (author) / LIU JIAQI (author) / HUANG JINYUAN (author) / ZOU SHIJIE (author) / WANG ZIHAO (author) / HUANG ZHENLIN (author) / LIU ZHENYU (author) / MA HENGSHAN (author)

    Publication date :

    2025-04-25


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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