Personal abnormal behavior detection method and device

• Main Authors: JI LI, GE SHENGLI, ZHONG DANYANG, QIAN QINYING, WEI GUOFU
• Format: Patent
• Language: Chinese; English
• Published: 01.09.2020
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention provides a personal abnormal behavior detection method and device. The method comprises the steps of 1) obtaining a stable sequence corresponding to original data of a to-be-detected user; 2) determining a corresponding baseline constant value by using a simple average algorithm for the stationary sequence of which the data length is smaller than a first preset threshold in the stationary sequences; 3) training a target ARIMA model for a stationary sequence of which the data length is not less than a first preset threshold in the stationary sequences, and predicting a predicted value of the user to be detected by using the target ARIMA model; 4) predicting a predicted value of the to-be-detected user by using an exponential smoothing method prediction baseline model; and 5) selecting an optimal model from the target ARIMA model and the exponential smoothing method prediction baseline model as a baseline model, and identifying abnormal users in the to-be-detected users byusing the baseline model.