Abnormity detection method and device, computer equipment and storage medium

An anomaly detection and anomaly technology, applied in the field of artificial intelligence, can solve the problem of low detection accuracy

Pending Publication Date: 2020-03-17
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology

[0003] In order to solve the technical problem in the prior art that the detection accuracy of significant periodic indicators is not high, the application provides an abnormality detection method, device, computer equipment and storage medium

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  • Abnormity detection method and device, computer equipment and storage medium
  • Abnormity detection method and device, computer equipment and storage medium
  • Abnormity detection method and device, computer equipment and storage medium

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Embodiment Construction

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of this application.

[0030] The flowchart shown in the drawings is only an example, and does not necessarily include all contents and operations / steps, nor does it have to be performed in the described order. For example, some operations / steps can also be decomposed, combined or partially combined, so the actual execution order may be changed according to actual conditions.

[0031] It should be understood that the terms used in the specification of this application are only for the p...

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Abstract

The invention relates to the technical field of artificial intelligence, and particularly discloses an abnormity detection method and device, computer equipment and a storage medium. The method comprises the following steps: if a to-be-detected index is a periodic significant index, obtaining historical prediction data corresponding to a plurality of time points before a preset time point of the to-be-detected index; inputting the plurality of historical prediction data into a prediction model to obtain a dynamic prediction result corresponding to a preset time point; obtaining a monitoring result corresponding to a preset time point, and calculating a residual error between the dynamic prediction result and the monitoring result; if the residual error exceeds a preset range, recording a monitoring result into an abnormal log, and detecting whether an abnormal event exists or not based on the abnormal log; and if the abnormal event exists, sending an abnormal event alarm to the operation and maintenance terminal. According to the method, based on the prediction result of the periodic significant index and the actual monitoring result, abnormity can be found in the hidden danger stage and manual troubleshooting is notified so as to avoid real system faults caused by subsequent fault hidden dangers.

Description

Technical field [0001] This application relates to the field of artificial intelligence technology, and in particular to an abnormality detection method, device, computer equipment and storage medium. Background technique [0002] In intelligent operation and maintenance monitoring and management, anomaly detection is an important part of the entire link. Because it is difficult to provide a large number of abnormal annotations for monitoring index sequences, the existing detection methods are mainly based on unsupervised learning algorithms or statistical algorithms, and there are also deep learning algorithms. However, the existing algorithms do not have high accuracy in detecting certain indicators (such as indicators with significant periodicity). When such indicators are abnormal but not obvious enough, they cannot be detected. Summary of the invention [0003] In order to solve the technical problem in the prior art that the detection accuracy of periodically significant in...

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Application Information

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IPC IPC(8): G06F11/34
CPCG06F11/3447G06F11/3476
Inventor 陈桢博金戈徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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