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Abnormal value detection method and device, electronic equipment and readable storage medium

A detection method and outlier technology, applied in the field of data analysis, can solve problems such as unrecognizable mutation values

Pending Publication Date: 2021-11-30
湖北天天数链技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present application is to provide an abnormal value detection method, device, electronic equipment and readable storage medium to solve the problem that the 3δ method in the prior art cannot identify the sudden change value

Method used

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  • Abnormal value detection method and device, electronic equipment and readable storage medium
  • Abnormal value detection method and device, electronic equipment and readable storage medium
  • Abnormal value detection method and device, electronic equipment and readable storage medium

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Experimental program
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Embodiment 1

[0038]In order to solve the prior art, the 3δ method cannot identify the problem of larger data, and the present application provides an abnormal value detection method. Below, combined figure 1 A flow chart of an abnormal value detection method is a description of an abnormal value detection method provided in the present application embodiment.

[0039] See figure 1 As shown, in the present application embodiment, an abnormal value detection method is provided, including:

[0040] S101, get the current time of the data set.

[0041] It should be noted that the current time's data set is a collection of data arranged in time, so that the data is arranged in the time sequence of the acquired data set. For the current K time, the data set of the current time can be expressed as: Among them, DATA k The data obtained at the time of the kth.

[0042] It should be noted that in this application, the maximum number of elements in the data set can be set in advance. For example, the num...

Embodiment 2

[0091] In order to facilitate understanding of the present application, the present embodiment can be used after performing step S101, after executing step S101, after obtaining the data set of the current time, Image 6 The process shown is anomalous value detection:

[0092] S601, if the data in the data set meets the normal distribution, determine the second 3 δ value and the second mean of the data set.

[0093] It will also be noted that it is the same manner that determines the normal distribution of the data set to meet the normal distribution of the differential data set, and will not be described herein.

[0094] S602, if the absolute value of the data and the second mean difference between the current time is greater than the second 3 δ value, the data of the current time is an exception value.

[0095] It should be noted that the absolute value of the data and the second ape value of the current time is greater than the second 3 δ value, ie | DATA K - The second mean |> ...

Embodiment 3

[0100] Based on the same inventive concept, the present application also provides an abnormal value detecting device 700, see Figure 7 Indicated. It should be understood that the device 700 can refer to the description above, in order to avoid repetition, will be described in detail herein. Device 700 includes a software function module in which at least one can be stored in a memory in a memory in a memory or in the operating system of device 700. specifically:

[0101] See Figure 7 As shown, device 700 includes: acquiring module 701 and determining module 702. in:

[0102] Get module 701 for obtaining a data set at the current time;

[0103] The module 701 is also used to perform differential operations for the data set at the current time, and obtain differential data sets;

[0104] Determine module 702, for determining the differential data set to meet the normal distribution, determine the first 3 δ value and the first mean of the differential data set;

[0105] Determine mod...

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Abstract

The invention provides an abnormal value detection method and device, electronic equipment and a readable storage medium. The method comprises: obtaining a data set at a current moment; performing differential operation on the data set at the current moment to obtain a differential data set; if it is determined that the differential data set meets normal distribution, determining a first 3 delta value and a first mean value of the differential data set; and if the absolute value of the differential data at the current moment and the first mean value difference is greater than the first 3 delta value, determining that the differential data at the current moment is abnormal data. In the application, the differential operation is performed on the data set at the current moment to obtain the differential data set, so that whether the differential data at the current moment is the abnormal data or not is determined based on the differential data set, and identification of data with relatively large change can be realized.

Description

Technical field [0001] Technical Field The present invention relates to data analysis, particularly to a method of detecting an abnormal value, means, and an electronic device readable storage medium. Background technique [0002] At present, the commonly used method is 3δ outlier detection methods, i.e., the time series data sets collected if the normal distribution, standard deviation δ of the data set is calculated and the mean μ and the standard deviation multiplied by δ 3 3δ as the threshold value. If the absolute value of the difference between the mean μ and the current time data is greater than a threshold value, it is determined that the data is an abnormal value. [0003] 3δ and the current methods for the mean μ is smaller than the absolute value of the difference equal to the threshold, but it can not achieve effective compared to identify mutants having a larger value of mutation at a previous time. And this mutated value, usually outliers. For example, for boiler he...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/211G06F18/214
Inventor 杨波时宝旭李文勇
Owner 湖北天天数链技术有限公司