Polar Motion Prediction Based on the Combination of Weighted Least Squares and Vector Autoregressive Models
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6944-9_15
Reference10 articles.
1. Dill R, Dobslaw H (2010) Short-term polar motion forecasts from earth system modelling data. J Geodesy 84(9):529–536
2. Su XQ, Liu LT, Houtse H et al (2014) Long-term polar motion prediction using normal time-frequency transform. J Geodesy 88(2):145–155
3. Guo JY, Li YB, Dai CL et al (2013) A technique to improve the accuracy of Earth orientation prediction algorithms based on least squares extrapolation. J Geodyn 70:36–48
4. Xu XQ, Zhou YH (2019) EOP prediction using least square fitting and autoregressive filter over optimized data intervals. Adv Space Res 56(10):2248–2253
5. Schuh H, Ulrich M, Egger D et al (2002) Prediction of Earth orientation parameters by artificial neural networks. J Geodesy 76(5):247–258
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