An Application of Online Learning to Spacecraft Memory Dump Optimization

An Application of Online Learning to Spacecraft Memory Dump Optimization

In this paper, we present a real-world application of online learning with expert advice to the field of Space Operations, testing our theory on real-life data coming from the Copernicus Sentinel-6 satellite. We show that in Spacecraft Memory Dump Optimization, a lightweight Follow-The-Leader algori...

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Veröffentlicht in:arXiv.org 2022-09
Hauptverfasser: Cesari, Tommaso, Pergoli, Jonathan, Maestrini, Michele, Pierluigi Di Lizia
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Distance learning
Machine learning
Optimization
Spacecraft
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Zusammenfassung:In this paper, we present a real-world application of online learning with expert advice to the field of Space Operations, testing our theory on real-life data coming from the Copernicus Sentinel-6 satellite. We show that in Spacecraft Memory Dump Optimization, a lightweight Follow-The-Leader algorithm leads to an increase in performance of over \(60\%\) when compared to traditional techniques.
ISSN:2331-8422