Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence) - Tapa dura

 
9783030202118: Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence)
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ISBN 10: 3030202119 ISBN 13: 9783030202118
Editorial: Springer, 2019

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2019
Idioma
Inglés
ISBN 10 
3030202119
ISBN 13 
9783030202118
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
242
Editor
Hassanien Aboul Ella, Darwish Ashraf, El-Askary Hesham
Contacto del fabricante
no disponible
Persona responsable
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Alemania

Otras ediciones populares con el mismo título

9783030202149: Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence)

Edición Destacada

ISBN 10:  3030202143 ISBN 13:  9783030202149
Editorial: Springer, 2020
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