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Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence) - Tapa blanda
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.
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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.
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Machine Learning and Data Mining in Aerospace Technology
Publicado por
Springer International Publishing, 2020
ISBN 10: 3030202143
ISBN 13: 9783030202149
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Librería: moluna, Greven, Alemania
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Condición: 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. Nº de ref. del artículo: 448675040
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Machine Learning and Data Mining in Aerospace Technology (Studies in Computational Intelligence, 836)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Condición: New. In. Nº de ref. del artículo: ria9783030202149_new
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Machine Learning and Data Mining in Aerospace Technology
Publicado por
Springer International Publishing Aug 2020, 2020
ISBN 10: 3030202143
ISBN 13: 9783030202149
Nuevo
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783030202149
Cantidad disponible: 2 disponibles
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Machine Learning and Data Mining in Aerospace Technology
Publicado por
Springer International Publishing, 2020
ISBN 10: 3030202143
ISBN 13: 9783030202149
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783030202149
Cantidad disponible: 1 disponibles
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Machine Learning and Data Mining in Aerospace Technology
Publicado por
Springer International Publishing, Springer International Publishing Aug 2020, 2020
ISBN 10: 3030202143
ISBN 13: 9783030202149
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783030202149
Cantidad disponible: 2 disponibles
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Machine Learning and Data Mining in Aerospace Technology (Studies in Computational Intelligence, 836)
Librería: California Books, Miami, FL, Estados Unidos de America
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Condición: New. Nº de ref. del artículo: I-9783030202149
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Machine Learning and Data Mining in Aerospace Technology (Studies in Computational Intelligence, 836)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Condición: New. Nº de ref. del artículo: ABLIING23Mar3113020009574
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Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence)
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Condición: New. pp. 232. Nº de ref. del artículo: 26379985557
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Machine Learning and Data Mining in Aerospace Technology: 836 (Studies in Computational Intelligence)
Librería: Majestic Books, Hounslow, Reino Unido
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Condición: New. pp. 232. Nº de ref. del artículo: 382837066
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Machine Learning and Data Mining in Aerospace Technology
Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. 240 pages. 9.25x6.10x0.57 inches. In Stock. Nº de ref. del artículo: x-3030202143
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