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A method for detecting outliers in time series

A technology of time series and detection method, which is applied in the field of detection of abnormal points in time series, can solve the problems that abnormal data points cannot be accurately detected, and data information anomalies cannot be mined, and achieve the effect of good detection effect and high recall rate.

Inactive Publication Date: 2019-03-29
中国民用航空上海航空器适航审定中心
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Problems solved by technology

[0005] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the technical solution of the present invention is that the prior art cannot dig out the abnormality in the data information, even if it can dig out the information abnormality, the algorithm used is to find the abnormality in the time series database There are few algorithms that directly detect abnormal data points, such as abnormal data points in long-term series or streaming data cannot be accurately detected

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  • A method for detecting outliers in time series
  • A method for detecting outliers in time series
  • A method for detecting outliers in time series

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Embodiment Construction

[0059] Such as figure 1 As shown, the detection method of time series abnormal points in the embodiment of the present invention includes the following steps:

[0060] S1: discretize the original time series and obtain a symbol string;

[0061] S2: Mark the data in the symbol string to form a symbolized training data set;

[0062] S3: Construct a probability suffix tree based on the symbolized training data set;

[0063] S4: Detect abnormal points in the data sequence to be detected according to the probability suffix tree.

[0064] It should be noted that in step S1 of this embodiment, the length of the original time series is determined according to the actual situation and needs to be continuous. Step S1 specifically includes the following steps:

[0065] S11: Using the PAA method to represent the original time series to form several PAA segments, and the several PAA segments are in one-to-one correspondence with the data points of the original time series;

[0066] S1...

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Abstract

The technical proposal of the invention discloses a method for detecting abnormal points in time series, comprising the following steps: S1, discretizing an original time series and obtaining a symbolstring; 2, marking that data in the symbol string to form a symbolic train data set; S3, constructing a probability suffix tree according to the symbolized training data set; S4: detecting an abnormal point in the data sequence to be detected according to the probability suffix tree. A method for detecting time series anomaly point in that technical proposal of the invention can find out the anomaly mode which deviates from the conventional mode, can reveal the hidden information of the data more accurately and solve many practical problems. Time series can be expressed as probability suffixtree after being converted into symbol string by discretization processing. the emethod is more concise and more efficient to calculate the probability of suffix symbol of different symbol string, andthe recall ratio is high, and the detection effect is good.

Description

technical field [0001] The invention relates to the field of data detection, in particular to a method for detecting abnormal points in time series. Background technique [0002] Time series data is a form of data that occurs frequently in everyday applications. It has a wide range of applications in various fields such as aerospace, medical data analysis, financial data analysis, network abnormal behavior detection, and weather forecasting. In these application fields, frequent patterns in the mining sequence may not be able to reveal the abnormal information hidden in the data behavior, but these abnormal information can usually reflect certain problems. For example, abnormal data in the user's daily operation information may mean that the account password Compromised or compromised accounts. Anomalies in healthcare data may indicate that a disease is spreading. If the abnormalities in the information cannot be excavated, it is impossible to make reasonable decisions in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/22
Inventor 蔡喁
Owner 中国民用航空上海航空器适航审定中心
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