Missing data recovery method and device
A technology for missing data and recovery methods, applied in the field of data processing, can solve problems such as inability to perform principal component analysis, large reconstruction, and inaccurate principal components
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Embodiment approach 1
[0020] In this embodiment, it is assumed that missing data is included in multiple sets of data.
[0021] figure 1 A flowchart showing a method for recovering missing data according to Embodiment 1 of the present invention.
[0022] refer to figure 1 , firstly in step S110, multiple sets of data are acquired and combined into a corresponding numerical matrix. Specifically, multiple sets of data are acquired from a data source. In one embodiment, the data source is one or more monitoring devices, that is, in this step, multiple sets of monitoring data are obtained in time sequence from one or more monitoring devices as the multiple sets of data.
[0023] For example, assuming that multiple groups of data are the SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control) data shown in the following table 1, then in this step, obtain the data in time sequence from a plurality of sensors as monitoring equipment Multiple sets of data are composed ...
Embodiment approach 2
[0056] In this embodiment, not only the missing data in the multiple sets of data is restored, but also data compression is performed on the multiple sets of data.
[0057] figure 2 A flow chart showing a method for recovering missing data according to Embodiment 2 of the present invention.
[0058] like figure 2 As shown, in this embodiment, in addition to the steps S110-S150 for realizing the recovery of missing data in the first embodiment, it also includes steps S260 and S270 for realizing data compression and decompression. Regarding steps S110-S150, no detailed description is given here.
[0059] In step S260, the multiple sets of data are compressed using the result of the probability matrix decomposition.
[0060] Specifically, based on the following formula (4), the result of the probability matrix decomposition in step S120 is combined with the second factor matrix V obtained in step S120 k Multiply to perform data dimensionality reduction compression:
[0061...
Embodiment approach 3
[0072] image 3 A block diagram of a device for recovering missing data according to Embodiment 3 of the present invention is shown.
[0073] like image 3 As shown, the missing data recovery device 300 of this embodiment includes: a data acquisition unit 310 , a probability matrix decomposition unit 320 , a missing location determination unit 330 , a missing data obtaining unit 340 and a data recovery unit 350 .
[0074] The data acquisition unit 310 acquires multiple sets of data and composes them into a corresponding numerical matrix. Specifically, the data acquisition unit 310 acquires multiple sets of data from a data source. In one embodiment, the data source is one or more monitoring devices, that is, the data acquisition unit 310 acquires multiple sets of monitoring data from one or more monitoring devices in time sequence as the multiple sets of data.
[0075] In addition, as required, the data acquisition unit 310 also performs preprocessing such as data type conv...
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