Method and device for positioning training starting node of time sequence

A time series and start node technology, applied in the computer field, can solve problems such as inappropriate selection of training start nodes, and achieve the effect of improving accuracy and high efficiency

Pending Publication Date: 2021-06-08
BEIJING WODONG TIANJUN INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the embodiment of the present invention provides a time series training start node positioning method and device to solve the technical problem of inappropriate selection of the training start node

Method used

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  • Method and device for positioning training starting node of time sequence
  • Method and device for positioning training starting node of time sequence
  • Method and device for positioning training starting node of time sequence

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Embodiment Construction

[0067] Exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0068] In the prior art, there is no fixed or clear effective method for intercepting and selecting the starting node of the training set, and the following three methods are generally adopted:

[0069] (1) Use all the data, do not select the starting node of the training set data.

[0070] (2) Use an intuitive method to select the start node of the training set data, for...

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Abstract

The invention discloses a method and device for positioning a training starting node of time sequence, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: dividing a time sequence into a plurality of subsequences according to a preset number of segments; taking the sub-sequence closest to a prediction time node in the plurality of subsequences as a reference sequence, and respectively calculating the similarity between the reference sequence and the remaining subsequences in the plurality of subsequences; and according to the similarity between the reference sequence and the remaining subsequences in the plurality of subsequences, positioning the training starting node of the time sequence. According to the embodiment, the technical problem that the selection of the training starting node is improper can be solved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method and device for locating a time series training start node. Background technique [0002] When forecasting time series, the choice of training start node is very important, especially when the time series is long. If the training start node is far away, when there is a large difference between the historical data and the recent time series distribution, the long-term historical data will interfere with the prediction, and the distribution trend of the prediction results is not consistent with the distribution trend of the recent time series. At the same time, more data is used, which will cause more waste of storage and computing resources. When the training start node selection is relatively close and the historical distribution is similar to the recent time series, if the training set ignores the historical data and only retains the recent data, since the recent data...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F16/2458
CPCG06F16/2474G06F18/22
Inventor 张奔
Owner BEIJING WODONG TIANJUN INFORMATION TECH CO LTD
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