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Lei Yu, Zhao Danning, Cai Hongbing. A Least Squares Extrapolation Model for UT1-UTC Prediction Method with Consideration of the Edge-effect[J]. Astronomical Research and Technology, 2018, 15(3): 302-307.
Citation: Lei Yu, Zhao Danning, Cai Hongbing. A Least Squares Extrapolation Model for UT1-UTC Prediction Method with Consideration of the Edge-effect[J]. Astronomical Research and Technology, 2018, 15(3): 302-307.

A Least Squares Extrapolation Model for UT1-UTC Prediction Method with Consideration of the Edge-effect

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  • Received Date: December 13, 2017
  • Revised Date: December 24, 2017
  • Available Online: November 20, 2023
  • The prediction accuracy of UT1-UTC can be easily affected by the edge distortion of least squares (LS) fitting time-series, referred to as edge-effect in the data-processing domain, when periodic oscillations and residuals are separated by LS fitting. In order to alleviate the edge-effect, the original UT1-UTC time-series is first extended on both boundaries by using a time-series analysis model in this paper. A LS extrapolation model is then set up using the extended time-series. Finally UT1-UTC predictions are obtained by employing the combination of the edge-effect correlated least squares (ECLS) model and a stochastic predication technology such as neural network (NN). The numerical experiments demonstrate that the edge-effect can be noticeably alleviated with the developed method. In addition, the accuracy of the UT1-UTC short-term predictions is comparable with that by the conventional LS extrapolation-based prediction algorithm. However, the medium- and long-term predictions are significantly more accurate than those obtained by the proposed ECLS extrapolation-based prediction solution.
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