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Ultra Short-term Prediction of Pole Coordinates via Combination of Empirical Mode Decomposition and Neural Networks


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Chen, S., Cowan, C.F.N. and Grant, P.M. (1991). Orthogonal Least Squares Learning Algorithm for Radial Basis Function Networks. IEEE Transactions on Neural Networks, Vol. 2, No. 2, 302-309.Search in Google Scholar

Flandrin, P., Rilling, G. and Goncalvés, P. (2004). Empirical Mode Decomposition as a Filter Bank, IEEE SIGNAL PROCESSING LETTERS, Vol. 11, No. 2, 112-114.Search in Google Scholar

Gambis, D. and Luzum, B. (2011). Earth Rotation Monitoring, UT1 Determination and Prediction. Metrologia, Vol. 48, No. 4, 165-170.10.1088/0026-1394/48/4/S06Search in Google Scholar

Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998). The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis. Proceedings of the Royal Society London: A, Vol. 454, 903-995.10.1098/rspa.1998.0193Search in Google Scholar

Huang, N.E., Wu, M.L., Qu, W., Long, S.R. and Shen, S.S.P.H. (2003). Application of Hilbert-huang Transform to Non-Stationary Financial Time Series Analysis. Applied Stochastic Models in Business and Industry, Vol. 19, No. 3, 245-268.Search in Google Scholar

Kalarus, M., Kosek, W., Schuh, H. (2008). Summary of the Earth Orientation Parameters Prediction Comparison Campaign. EGU General Assembly 2008, EGU abstract: EGU2008-A-00595.Search in Google Scholar

Kalarus, M., Schuh, H., Kosek, W., Akyilmaz, O. and Bizouard, Ch. (2010). Achievements of the Earth Orientation Parameters Prediction Comparison Campaign. Journal of Geodesy, Vol. 84, No. 10, 587-596.10.1007/s00190-010-0387-1Search in Google Scholar

Kosek, W. (2011). Future Improvements in EOP Prediction. Geodesy for Plant Earth, International Association of Geodesy Symposia, Vol. 136, 513-520.Search in Google Scholar

Kosek, W., Kalarus, M., Johnson, T.J., Wooden, W.H., McCarthy, D.D. and Popiński, W. (2005). A Comparison of LOD and UT1-UTC Forecasts by Different Combined Prediction Techniques. Artificial Satellites, Vol. 40, No. 2, 119-125.Search in Google Scholar

Kurkova, V. (1992). Kolmogorov’s Theorem and Multilayer Neural Networks. Neural Networks, Vol. 5, No. 3, 501-506.10.1016/0893-6080(92)90012-8Search in Google Scholar

Lei, Y., Zhao, D.N. and Cai, H.B. (2015). Extreme Learning Machines for the Predictions of Length of Day. Artificial Satellites, Vol. 50, No. 1, 19-33.10.1016/j.geog.2014.12.007Search in Google Scholar

Liao, D.C., Wang, Q.J., Zhou, Y.H., Liao, X.H. and Huang, C. L. (2012). Long-term Prediction of the Earth Orientation Parameters by the Artificial Neural Network Technique. Journal of Geodynamics, Vol. 62, No. 8, 87-92.Search in Google Scholar

Park, J. and Sandberg, I.W. (1991). Universal Approximation Using Radial-Basis-Function Networks. Neural Computing, Vol. 3, No. 2, 246-257.10.1162/neco.1991.3.2.24631167308Search in Google Scholar

Schuh, H., Ulrich, M., Egger, D., Müller, J. and Schwegmann, W. (2002). Prediction of Earth Orientation Parameters by Artificial Neural Networks. Journal of Geodesy, Vol. 76, No. 5, 247-258.10.1007/s00190-001-0242-5Search in Google Scholar

Wang, Q.J., Du, Y.N. and Liu, J. (2014). Introducing Atmospheric Angular Momentum into Prediction of Length of Day Change by Generalized Regression Neural Network Model. Journal of Central South University, Vol. 21, No. 4, 1396-1401.Search in Google Scholar

Wang, Q.J., Liao, D.C. and Zhou, Y.H. (2008). Real-Time Rapid Prediction of Variations of Earth’s Rotational Rate. Chinese Science Bulletin, Vol. 53, No. 7, 969-973.Search in Google Scholar

Xu, X.Q., Zotov, L. and Zhou, Y.H. (2012). Combined Prediction of Earth Orientation Parameters. China Satellite Navigation Conference (CSNC) 2012 Proceedings Lecture Notes in Electrical Engineering, Vol. 160, No. 2, 361-369.Search in Google Scholar

Zhang, X.H., Wang, Q.J., Zhu, J.J. and Zhang, H. (2012). Application of General Regression Neural Network to the Prediction of LOD Change. Chinese Astronomy and Astrophysics, Vol. 36, No. 1, 86-96.Search in Google Scholar

eISSN:
2083-6104
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Geosciences, other