Satellite Data Prediction Method Based on Improved Unbiased gm(1,1) Model

A prediction method and satellite data technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as poor accuracy of prediction results, and achieve the effect of smoothing and improving
CN104899457BInactive Publication Date: 2017-07-25NORTHWESTERN POLYTECHNICAL UNIV +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NORTHWESTERN POLYTECHNICAL UNIV
Publication Date
2017-07-25
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a satellite data prediction method based on an improved unbiased GM (1, 1) model, so as to solve the technical problems that the existing satellite data prediction methods are poor in accuracy of predicted results. The technical scheme thereof comprises the following steps: firstly preprocessing original satellite telemeasuring data, supplementing missing bits and deleting outlier data of the original satellite telemeasuring data; then normalizing and smoothening the preprocessed data; and then establishing the unbiased GM (1, 1) model, using the data processed by the steps above as input data for prediction, introducing the obtained new prediction results as information into the unbiased GM (1, 1) model for updating the prediction; and finally de-smoothening and de-normalizing the obtained prediction data to obtain the final prediction results. More accurate prediction results are obtained by the method through preprocessing the satellite telemeasuring data and using the newly obtained data to update the data inputted into the unbiased GM (1, 1) model.
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Description

technical field

[0001] The invention relates to a satellite data prediction method, in particular to a satellite data prediction method based on an improved unbiased GM (1,1) model. Background technique

[0002] The prediction method using the gray GM (1, 1) model is a system prediction method of uncertain factors based on poor information. It uses part of the data to model, extracts valuable information of the system, and predicts the unknown part of the data. However, when the traditional GM(1,1) model is used for forecasting, it is limited by the principle of the model, and the original data is required to be non-negative and stable data that changes according to an exponential law. The accuracy of the prediction results is poor, and because the traditional GM(1,1) model has deviations in the modeling process, it is necessary to propose an unbiased GM(1,1) model to eliminate the modeling deviation and make the prediction results more accurate.

[0003] The prediction of ...

Claims

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