Traffic anomaly detection method, and model training method and apparatus

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United States of America

PATENT NO 12237981
APP PUB NO 20220166681A1
SERIAL NO

17669638

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Abstract

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A traffic anomaly detection method includes obtaining a target time series including N elements; obtaining a target parameter of the target time series, where the target parameter includes at least one of a periodic factor or a jitter density, the periodic factor represents a wave-shaped change that is presented in the target time series and that is about a long-term trend, and the jitter density represents a deviation between an actual value and a target value of the target time series within a target time; determining, from a plurality of types based on the target parameter, a first type to which the target time series belongs, where each of the types corresponds to one parameter set, and the target parameter belongs to a parameter set corresponding to the first type; and detecting an anomaly of the target time series based on a first-type decision model corresponding to the first type.

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Patent Owner(s)

  • HUAWEI TECHNOLOGIES CO., LTD.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Li, Gang Chengdu, CN 629 4192
Lin, Wei Shenzhen, CN 588 4836
Xue, Li Nanjing, CN 50 162
Zhang, Yanfang Nanjing, CN 30 43

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