1. Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences Annual Seminar of Commission of Satellite Geodesy, EARTH ROTATION AND SATELLITE GEODESY - FROM ASTROMETRY TO GNSS Warsaw, 18-19 September 2003

2. In this poster the Neural Network Toolbox version 3.0.1 software of Matlab ver.5.3 was used to predict the IERS EOPC04 x, y pole coordinates data and obtained results were compared to the predictions of the IERS Sub- Bureau for Rapid Service and Prediction.

3. Prediction of x, y pole coordinates data by combination of the LS extrapolation and Neural Network prediction x, y LS extrapolation residuals Prediction of x, y LS extrapolation residuals LS extrapolation of x, y Prediction of x, y Neural Network x, y EOPC04 pole coordinates data x, y LS model

4. Polar motion model linear trend Chandler oscillation annual oscillation Polar motion model linear trend Chandler oscillation annual oscillation

5. Prediction of the x, y pole coordinates data by combination of the LS extrapolation and the NN prediction Fig. 10. The absolute values of the difference between x, y pole coordinates data and their prediction being the combination of the LS extrapolation and the NN prediction of the LS extrapolation residuals computed at different starting prediction epochs.

6. Fig. 11. The mean prediction error in 1984 - 2003.6 of the x, y pole coordinates data computed from combination of the LS extrapolation and the NN prediction of the LS extrapolation residuals as well as of the IERS Sub-Bureau for Rapid Service and Prediction. The mean prediction error