Method and device for time series abnormal pattern recognition based on fuzzy matching

A time series and pattern recognition technology, applied in the field of data processing, can solve problems such as the inability to identify abnormalities in light-varying brightness

Active Publication Date: 2022-03-15
TSINGHUA UNIV
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Problems solved by technology

However, in related technologies, it is still impossible to effectively identify many anomalies of light-varying brightness.

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  • Method and device for time series abnormal pattern recognition based on fuzzy matching
  • Method and device for time series abnormal pattern recognition based on fuzzy matching
  • Method and device for time series abnormal pattern recognition based on fuzzy matching

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Embodiment Construction

[0028] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0029] Before introducing the fuzzy matching-based time series anomaly pattern recognition method and device, the definition of pattern anomaly is given as follows:

[0030] In the embodiment of the present invention, an in-depth study can be performed by defining an abnormal pattern and searching in sequences to obtain real abnormal samples. Among them, the definition of mode anomaly is given: For multiple continuous brightness segments such as S1,...,Sn, etc., which have a high similarity with the mode of interest in the embodi...

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Abstract

The invention discloses a fuzzy matching-based time series abnormal pattern recognition method and device, wherein the method includes the following steps: performing missing value processing, white noise processing, and outlier processing on the original time series to obtain preset conditions time series; detect turning points in the time series that meet the preset conditions, so as to divide the time series that meet the preset conditions into multiple segmented subsequences; search based on the start and end points of each segmented subsequence The obtained sequence segment is matched by the DTW algorithm to obtain the matching result. This method does not need to precisely define all abnormal patterns, and only a small number of templates can search for interesting pattern fragments, and can achieve the purpose of sequential pattern search on the basis of appropriate scale and effectiveness.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a fuzzy matching-based time series abnormal pattern recognition method and device. Background technique [0002] In time-domain astronomy, it is necessary to deal with a large amount of stellar magnitude and brightness time series data, among which many anomalies of light variation and brightness represent valuable astronomical phenomena, such as microgravitational lensing and stellar flares, the light variation of the two There are more accurate mathematical model descriptions. However, in the related art, it is still impossible to effectively identify many anomalies of light variable brightness. Contents of the invention [0003] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. [0004] For this reason, an object of the present invention is to propose a time series abnormal pattern recognition method ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/00G06F16/2458
CPCG06F16/2468G06F16/2474G06F18/22
Inventor 马晓彬都志辉
Owner TSINGHUA UNIV
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