Machine Learning and Data Mining in Aerospace Technology / Studies in Computational Intelligence Bd.836 (PDF)
(Sprache: Englisch)
This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the 'eagle eyes' that allow us to view massive areas of the Earth simultaneously, and can gather more data, more...
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This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the 'eagle eyes' that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites - which can determine satellites' current status and predict their failure based on telemetry data - is one of the most important current issues in aerospace engineering.
This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.
Bibliographische Angaben
- 2019, 1st ed. 2020, 232 Seiten, Englisch
- Herausgegeben: Aboul Ella Hassanien, Ashraf Darwish, Hesham El-Askary
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030202127
- ISBN-13: 9783030202125
- Erscheinungsdatum: 02.07.2019
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 8.17 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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