Neural network in predicting the Earth rotation
| Authors: Gorbachevskaya A.P. |  |
| Published in issue: #3(92)/2024 | |
| DOI: | |
Category: Physics | Chapter: Astrophysics |
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Keywords: neural network, neural network approach, forecasting, Earth rotation, Earth orientation models, International Earth Rotation Service (IERS), recurrent neural networks |
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| Published: 17.07.2024 | |
The paper compares the International Earth Rotation Service (IERS) forecast with the forecasts obtained using a neural network. For this purpose, the pole position data obtained from the IERS source are used. The forecast results are being compared using the different recurrent neural network architectures in order to assess accuracy and efficiency of the neural network approach. The paper pays particular attention to analyzing differences between the IERS forecasts and the neural network forecasts, as well as to identifying the neural network probable advantages in this area. The paper concludes on the prospects for introducing a neural network in developing the more accurate Earth orientation models.
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