Time series processing method and time series processing device

Abstract

An embodiment of the invention provides a time series processing method and a time series processing device and relates to the technical field of data mining. The time series processing method includes acquiring a target parameter time series of target parameters including parameters to be detected within a preset time length; then acquiring an influence factor time series of the target parameters within the preset time duration; finally, selecting a dynamic similarity series of the parameters to be detected from M subseries of the target parameters based on the target parameter time series and the influence factor time series. The time series processing method has the advantage that change processes of the target parameters and all influence factors thereof are included into selection rules of similar time series comprehensively, and similar time series selection accuracy and time series predication accuracy are both higher in time series prediction affected by accumulative effects, so that prediction errors of the time series in the prior art are reduced effectively.

Description

technical field [0001] The present invention relates to the technical field of data mining, in particular to a time series processing method and device. Background technique [0002] In the existing research on time series forecasting using similar time series method, most of the changes of the target parameters are deduced and studied as the change rules of time series, and this rule is considered to be fixed. But in reality, this pattern is time-varying. Therefore, there is a technical problem in the prior art that the prediction error is still relatively large. Contents of the invention [0003] The present invention provides a time series processing method and device, aiming to improve the above technical problems. [0004] A time series processing method provided by the present invention includes: acquiring a target parameter time series containing target parameters of parameters to be measured within a preset time length, wherein the target parameter time series in...

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Problems solved by technology

Therefore, there is a technical problem that the prediction error is still relatively large in the prior art

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