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Abnormal monitoring method and system for time series data

A technology of abnormal monitoring and time series data, applied in the field of data processing, can solve the problems of lack of trend data statistical attributes, reduce the accuracy and reliability of data monitoring sample data, etc., to improve reliability, improve accuracy, and improve processing efficiency Effect

Active Publication Date: 2020-08-28
AISPEECH CO LTD
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  • Claims
  • Application Information

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Problems solved by technology

The lack of statistical attributes for trend data reduces the accuracy and reliability of data monitoring sample data

Method used

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  • Abnormal monitoring method and system for time series data
  • Abnormal monitoring method and system for time series data
  • Abnormal monitoring method and system for time series data

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Embodiment Construction

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0047] In the following, the embodiment of the present application will be introduced first, and then the experimental data will be used to verify the difference between the solution of the present application and the prior art, and what beneficial effects can be achieved.

[0048] English full names and Chinese definitions of English abbreviation...

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Abstract

The invention discloses a time sequence data exception monitoring method and system, and the method comprises the steps: removing an exception value in historical periodic monitoring data, and obtaining historical periodic monitoring smooth data; performing periodic decomposition according to the historical periodic monitoring smooth data to obtain multi-period change trend data and a periodic change data sequence; training the change trend data through an ARIMA model to obtain a trend value of a set prediction time end; according to the trend value and the predicted periodical change data sequence value, training through a random forest algorithm, and generating a final predicted value; and setting a monitoring threshold value according to the final prediction value, and monitoring the data of the set prediction time end. According to the invention, the characteristics of the trend change data are introduced into the attributes of the monitoring data by analyzing the time sequence ofmultiple periods of the time sequence data, so that the reliability of the threshold value of the monitoring data is improved. Therefore, the implementation of the machine learning method is more convenient.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to an abnormality monitoring method and system of time series data. Background technique [0002] At present, for the abnormal monitoring of periodic data, the most solutions on the market are to use statistical methods such as comparison with the same period, set thresholds based on experience, or time series analysis methods (moving average model (MA, moving average) or ARMA) to predict the data of the next period, and then monitor abnormalities by setting thresholds. Some, predict and monitor by establishing a neural network (Long Short-Term Memory, long-term short-term memory network) model. [0003] The year-on-year forecast is mainly to compare the data of the same period in the past, such as comparing the data of this Friday with the data of last Friday. If it exceeds a certain threshold (determined based on experience), it is considered abnormal data. M...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2458
Inventor 覃江陈琪瑶
Owner AISPEECH CO LTD