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Synopsis
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.
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Machine Learning and Data Mining in Aerospace Technology
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Springer International Publishing, 2020
ISBN 10 : 3030202143
ISBN 13 : 9783030202149
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores the main concepts, algorithms, and techniques of machine learning and data mining for aerospace technology  Provides essential information on data mining and machine learning for satellite monitoring&nb. N° de réf. du vendeur 448675040
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Machine Learning and Data Mining in Aerospace Technology (Studies in Computational Intelligence, 836)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Machine Learning and Data Mining in Aerospace Technology
Edité par
Springer International Publishing, 2020
ISBN 10 : 3030202143
ISBN 13 : 9783030202149
Neuf
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783030202149
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Machine Learning and Data Mining in Aerospace Technology
Edité par
Springer International Publishing Aug 2020, 2020
ISBN 10 : 3030202143
ISBN 13 : 9783030202149
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Machine Learning and Data Mining in Aerospace Technology
ISBN 10 : 3030202143
ISBN 13 : 9783030202149
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