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Missing value filling method and device for time series data

A technology of time series and sequence data, which is applied in the computer field and can solve problems such as equipment communication errors

Active Publication Date: 2020-04-21
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to problems such as equipment failures and communication errors in real scenarios, there are often many missing values ​​in real time series data

Method used

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  • Missing value filling method and device for time series data
  • Missing value filling method and device for time series data

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Embodiment Construction

[0026] The present disclosure will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0027] It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

[0028] figure 1 An exemplary system architecture 100 to which the method for filling missing values ​​of time series data or the apparatus for filling missing values ​​of time series data of the present disclosure can be applied is shown.

[0029] like figure 1 As sho...

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Abstract

The invention relates to the field of cloud computing. The embodiment of the invention provides a missing value filling method and device for time series data. The method comprises: acquiring originaltime series data containing missing values and mask series data corresponding to the original time series data, wherein the mask series data are used for identifying the positions of the missing values in the original time series data; filling missing values in the original time series data into preset numerical values, and inputting the original time series data filled with the preset numericalvalues and the corresponding mask series data into a data filling model to obtain filled time series data containing prediction numerical values of the missing values in the original time series data,wherein the data filling model comprises a generator in the trained generative adversarial network, and a discriminator in the generative adversarial network is used for discriminating whether the time series data generated by the data filling model is real time series data. According to the method, the filling precision of the missing value of the time series data is improved.

Description

technical field [0001] The embodiments of the present disclosure relate to the field of computer technology, specifically to the field of cloud computing, and in particular to a method and device for filling missing values ​​of time series data. Background technique [0002] Time series data is a series of values ​​distributed over time. With the development of cloud computing and Internet of Things technology, time-series data is becoming more and more common, such as temperature, industrial sensor data, stock prices, server status parameters (such as CPU and memory usage), and so on. Due to problems such as equipment failures and communication errors in real scenarios, there are often many missing values ​​in real time series data. These missing values ​​have a valid impact on subsequent applications such as statistical analysis. Contents of the invention [0003] Embodiments of the present disclosure provide a method and device for filling missing values ​​of time ser...

Claims

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Application Information

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IPC IPC(8): G06F16/215G06F16/2458G06N3/04G06N3/08
CPCG06F16/215G06F16/2474G06N3/08G06N3/045Y04S10/50
Inventor 孟泉
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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