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Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence, 836) - Hardcover
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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From the Back Cover
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 (Studies in Computational Intelligence, 836, Band 836) [Hardcover] Hassanien, Aboul Ella; Darwish, Ashraf and El-Askary, Hesham
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Machine Learning and Data Mining in Aerospace Technology
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Machine Learning and Data Mining in Aerospace Technology
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Machine Learning and Data Mining in Aerospace Technology (Studies in Computational Intelligence, 836)
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Machine Learning and Data Mining in Aerospace Technology
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Condition: 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. Seller Inventory # 300510444
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Machine Learning and Data Mining in Aerospace Technology
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Machine Learning and Data Mining in Aerospace Technology
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 240 pp. Englisch. Seller Inventory # 9783030202118
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Machine Learning and Data Mining in Aerospace Technology
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ISBN 13: 9783030202118
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Buch. Condition: 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. Seller Inventory # 9783030202118
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Machine Learning and Data Mining in Aerospace Technology
ISBN 10: 3030202119
ISBN 13: 9783030202118
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Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch. Seller Inventory # 9783030202118
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