Cargando…
The Short-Term Prediction of Length of Day Using 1D Convolutional Neural Networks (1D CNN)
Accurate Earth orientation parameter (EOP) predictions are needed for many applications, e.g., for the tracking and navigation of interplanetary spacecraft missions. One of the most difficult parameters to forecast is the length of day (LOD), which represents the variation in the Earth’s rotation ra...
Autores principales: | Guessoum, Sonia, Belda, Santiago, Ferrandiz, Jose M., Modiri, Sadegh, Raut, Shrishail, Dhar, Sujata, Heinkelmann, Robert, Schuh, Harald |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740590/ https://www.ncbi.nlm.nih.gov/pubmed/36502228 http://dx.doi.org/10.3390/s22239517 |
Ejemplares similares
-
Inter-Comparison of UT1-UTC from 24-Hour, Intensives, and VGOS Sessions during CONT17
por: Raut, Shrishail, et al.
Publicado: (2022) -
Polar motion prediction using the combination of SSA and Copula-based analysis
por: Modiri, Sadegh, et al.
Publicado: (2018) -
A new hybrid method to improve the ultra-short-term prediction of LOD
por: Modiri, Sadegh, et al.
Publicado: (2020) -
Drift of the Earth’s Principal Axes of Inertia from GRACE and Satellite Laser Ranging Data
por: Ferrándiz, José M., et al.
Publicado: (2020) -
Towards Understanding the Interconnection between Celestial Pole Motion and Earth’s Magnetic Field Using Space Geodetic Techniques
por: Modiri, Sadegh, et al.
Publicado: (2021)