In view of the characteristics of the dynamic distribution of space big data with super long time series, the traditional time series model is difficult to effectively approximate or completely realize the state prediction and trend analysis of telemetry data covering the whole period. In this paper, the concept drift is combined with the autoregressive theory in time series analysis, and the hidden rules in telemetry data are mined from the perspective of multi-level and multi time scale, and a new solution to telemetry sequence prediction is proposed. This paper designs the prediction algorithm of telemetry sequence based on concept drift. By detecting the concept drift point of telemetry sequence, and on this basis, the multivariable autoregressive model is used to predict the future concept and the duration of telemetry sequence, so as to realize the prediction of telemetry sequence. The experimental results show that the proposed method has more accurate prediction effect.
Telemetry Parameter Prediction of Spacecraft Power System Based on Concept Drift
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021) ; Kapitel : 182 ; 1841-1852
2022-03-18
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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