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Method and device for acquiring KPI abnormal data sample and computer equipment

An abnormal data and data technology, which is applied in computer parts, computing, electrical digital data processing, etc., can solve the problem of time-consuming and labor-intensive marking of KPI abnormal samples, and achieve the effect of reducing marking time and reducing operation and maintenance costs

Active Publication Date: 2020-11-06
PING AN TECH (SHENZHEN) CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a method, device, computer equipment and storage medium for obtaining KPI abnormal data samples, aiming to solve the technical problem of time-consuming and labor-intensive marking of KPI abnormal samples in the prior art

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  • Method and device for acquiring KPI abnormal data sample and computer equipment
  • Method and device for acquiring KPI abnormal data sample and computer equipment
  • Method and device for acquiring KPI abnormal data sample and computer equipment

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Embodiment Construction

[0048] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0049] refer to figure 1 , the method for acquiring KPI abnormal data samples in this embodiment includes:

[0050] Step S1: Acquire KPI data for a preset time period, the KPI data is data of the time series data type, each piece of KPI data includes a plurality of data points, and each unit of time corresponds to one data point in chronological order;

[0051] Step S2: Perform anomaly detection on the KPI data to obtain corresponding potential anomalous data points, and take the potential anomalous data points as the end point, retroactively intercept a specified segment of KPI data in chronological order as candidate KPI anomalous data;

[0052] Step S3: Adjusting the candidate KPI abnormal data and the preset known KPI abnormal data, so that the candidate KPI abnormal data and the known KPI abnormal data correspond ...

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Abstract

The invention relates to an artificial intelligence technology, is applied to a smart city, and provides a method and device for acquiring a KPI abnormal data sample, computer equipment and a storagemedium. The method comprises the following steps: acquiring KPI data in a preset time period; carrying out anomaly detection on the KPI data to obtain a potential abnormal data point, and backtrackingand intercepting specified segment of KPI data as candidate KPI abnormal data according to a time sequence by taking the potential abnormal data point as an end point; adjusting the candidate KPI abnormal data and the known KPI abnormal data to enable the time lengths of the candidate KPI abnormal data and the known KPI abnormal data to be consistent, and performing similarity distance calculation on corresponding data points of the candidate KPI abnormal data and the known KPI abnormal data to obtain a plurality of regular path distances; judging whether the candidate KPI abnormal data are KPI abnormal data or not according to the regular path distances; and if so, marking the candidate KPI abnormal data as KPI abnormal data to serve as a sample for training the intelligent KPI abnormalrecognition model. A large number of KPI abnormal data samples are obtained through a small number of known KPI abnormal data samples, so that the operation and maintenance cost are greatly reduced.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a method, device, computer equipment and storage medium for acquiring KPI abnormal data samples. Background technique [0002] Internet services such as search engines and online shopping have become an integral part of our daily lives. To ensure uninterrupted business, operators usually need to closely monitor various KPIs (key performance indicators), such as search response time, CPU usage etc. to accurately detect KPI anomalies and initiate troubleshooting and resolution measures in a timely manner. [0003] KPI anomaly detection is a very important part in the field of intelligent operation and maintenance. In the field of intelligent operation and maintenance, KPI anomaly algorithms are usually used to predict KPI anomalies. This requires a large number of KPI anomaly sample data to help train and evaluate algorithms. However, at present, KPI data m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/30G06F11/34G06K9/62
CPCG06F11/3051G06F11/3452G06F18/22G06F18/214
Inventor 邓悦郑立颖徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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