Method, device and processing device for correcting abnormal data in time series

A technology for time series and abnormal data, applied in the field of data processing, can solve problems such as affecting the prediction accuracy of time series analysis models, reducing the prediction accuracy of time series analysis models, etc., to achieve the effect of improving efficiency and accuracy

Inactive Publication Date: 2018-11-20
ADVANCED NEW TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Abnormal data will affect the prediction accuracy of the entire time series analysis model. For example, if there are multiple

Method used

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  • Method, device and processing device for correcting abnormal data in time series
  • Method, device and processing device for correcting abnormal data in time series
  • Method, device and processing device for correcting abnormal data in time series

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Experimental program
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Effect test

Embodiment 1

[0053] In the prior art, after identifying the abnormal data of the time series, it is often necessary to manually correct the abnormal data manually. This not only affects efficiency, but also requires manual determination of the correction method for abnormal data. Therefore, manual experience and business level will have a certain impact on the correction result, resulting in low correction accuracy. Embodiment 1 of this specification provides a method for correcting abnormal data in a time series. figure 1 It is a schematic diagram of the method for correcting abnormal data in the time series of this embodiment. Such as figure 1 As shown, the method includes:

[0054] Step 101: Decompose the time series to at least decompose a first time series and a second time series, the first time series reflecting the change trend of the time series, and the second time series reflecting the irregular changes of the time series;

[0055] Step 102: Correct the first time series and / or the ...

Embodiment 2

[0097] Another embodiment of this specification provides a device for correcting abnormal data in a time series, and the same content of this embodiment 2 and embodiment 1 will not be repeated.

[0098] Picture 11 It is a schematic diagram of the structure of the device for correcting abnormal data in the time series of the second embodiment. Such as Picture 11 As shown, the device 1100 for correcting abnormal data in a time series includes: a decomposition part 1101, which decomposes the time series to at least decompose a first time series and a second time series, the first time series reflects changes in the time series Trend, the second time series reflects irregular changes in the time series; the correction part 1102, which corrects the first time series and the second time series respectively; the synthesis part 1103, which is based on the corrected first time series and / or the corrected The second time series generates a corrected time series.

[0099] According to this...

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Abstract

One embodiment of the description provides a method, device and processing device for correcting abnormal data in a time series. The method comprises: decomposing a time series, and at least decomposing out a first time series and a second time series, wherein the first time series reflects the change trend of the time series, and the second time series reflects the irregular change of the time series; correcting the first time series and/or the second time series respectively; and generating the corrected time series according to the corrected first time series and/or the corrected second time series. The technical scheme of the invention can automatically recognize the abnormal data in the time series and automatically correct the abnormal data, and can improve the efficiency and accuracy of correcting the abnormal data.

Description

Technical field [0001] The embodiments of this specification relate to the field of data processing technology, and in particular to a method, device and processing equipment for correcting abnormal data in a time series. Background technique [0002] Time series analysis is a widely used analysis method. Its main purpose is to predict the future based on existing historical data. It is usually used in national economic macro control, regional comprehensive development planning, business management, market potential prediction, and risk Operational control, weather forecast, hydrological forecast, earthquake precursor forecast, crop disease and insect disaster forecast, environmental pollution control, etc. [0003] In time series analysis, the detection and correction of abnormal data in time series is a fundamental and important issue in this field. Abnormal data will affect the prediction accuracy of the entire time series analysis model. For example, if there are multiple infl...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 李莹洁
Owner ADVANCED NEW TECH CO LTD
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