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Application of Wavelet Analysis in The Prediction of Telemetry Data

Jiangtao Xu

Jiangtao Xu

School of Computer Science and Engineering Xi’an Technological UniversityXi’an, China
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Xu, Jiangtao
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Pingping Liu

Pingping Liu

School of Computer Science and Engineering Xi’an Technological UniversityXi’an, China
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Liu, Pingping
  
Oct 08, 2019
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Published Online: Oct 08, 2019
Page range: 28 - 34
DOI: https://doi.org/10.21307/ijanmc-2019-044
Keywords
© 2019 Xu Jiangtao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Data of 1 consecutive 4 hours curve graph
Data of 1 consecutive 4 hours curve graph

Figure 2.

Data of 2 consecutive 4 hours curve graph
Data of 2 consecutive 4 hours curve graph

Figure 3.

Comparison results of dbN wavelet based N=1,2,3,4
Comparison results of dbN wavelet based N=1,2,3,4

Figure 4.

Comparison of different decomposition scale approximation section
Comparison of different decomposition scale approximation section

Figure 5.

Comparison results between predicted values and actual results
Comparison results between predicted values and actual results

Figure 6.

The comparison results between the predicted values and the actual values of the modified boundary
The comparison results between the predicted values and the actual values of the modified boundary

THE TEST RESULTS OF A REMOTE SENSING DATA 1 STATIONARITY

Time 24 60 120 240
Mean Value 608.618 620.9572 622.6287 622.6287
Variance 198.2080 604.1601 611.2902 674.6010

THE TEST RESULTS OF A REMOTE SENSING DATA 2 STATIONARITY

Time 24 60 120 240
Mean Value 29.2479 35.413 37.1234 39.2378
Variance 10.3366 30.9019 37.4902 42.5010
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Computer Sciences, other
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