GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data
Author:
Affiliation:
1. Bias Variance Labs,Ljubljana,Slovenia
2. LSE Space GmbH,Gilching,Germany
3. European Space Agency,ESOC,Darmstadt,Germany
4. Solenix Engineering,Darmstadt,Germany
5. Jožef Stefan Institute,Ljubljana,Slovenia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9697402/9697407/09697674.pdf?arnumber=9697674
Reference26 articles.
1. Predicting Thermal Power Consumption of the Mars Express Satellite with Machine Learning
2. Machine Learning for Predicting Thermal Power Consumption of the Mars Express Spacecraft
3. Machine Learning in Operations for the Mars Express Orbiter
4. Quantifying the Effects of Gyroless Flying of the Mars Express Spacecraft with Machine Learning
5. Machine Learning Modeling Methods for Radiation Belts Profile Predictions
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