Short-term prediction of celestial pole offsets with interpretable machine learning

Short-term prediction of celestial pole offsets with interpretable machine learning

Abstract The difference between observed and modelled precession/nutation reveals unmodelled signals commonly referred to as Celestial Pole Offsets (CPO), denoted by dX and dY. CPO are currently observed only by Very Long Baseline Interferometry (VLBI), but there is nearly 4 weeks of latency by whic...

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Bibliographic Details
Main Authors: Mostafa Kiani Shahvandi, Santiago Belda, Siddhartha Mishra, Benedikt Soja
Format: Article
Language:English
Published: SpringerOpen 2024-01-01
Series:Earth, Planets and Space
Subjects:
Celestial pole offsets
Interpretable machine learning
Neural additive models
Prediction accuracy
Online Access:https://doi.org/10.1186/s40623-024-01964-2

Internet

https://doi.org/10.1186/s40623-024-01964-2

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