Studies in Computational Intelligence

Machine Learning and Data Mining in Aerospace Technology

Editors: Hassanien, Aboul Ella, Darwish, Ashraf, El-Askary, Hesham (Eds.)

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  • 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 
  • Presents an experimental implementation of telemetry data processing to identify hidden events using various data mining techniques
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eBook 139,09 €
price for Spain (gross)
  • ISBN 978-3-030-20212-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 176,79 €
price for Spain (gross)
Softcover 124,79 €
price for Spain (gross)
About this book

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.

Table of contents (11 chapters)

Table of contents (11 chapters)
  • Tensor-Based Anomaly Detection for Satellite Telemetry Data

    Pages 3-16

    Ramadan, Alaa H. (et al.)

  • Machine Learning in Satellites Monitoring and Risk Challenges

    Pages 17-38

    Alielden, Khaled

  • Formalization, Prediction and Recognition of Expert Evaluations of Telemetric Data of Artificial Satellites Based on Type-II Fuzzy Sets

    Pages 39-64

    Poleshchuk, Olga M.

  • Intelligent Health Monitoring Systems for Space Missions Based on Data Mining Techniques

    Pages 65-78

    Abdelghafar, Sara (et al.)

  • Design, Implementation, and Validation of Satellite Simulator and Data Packets Analysis

    Pages 79-103

    Ezzat, Kadry Ali (et al.)

Buy this book

eBook 139,09 €
price for Spain (gross)
  • ISBN 978-3-030-20212-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 176,79 €
price for Spain (gross)
Softcover 124,79 €
price for Spain (gross)
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning and Data Mining in Aerospace Technology
Editors
  • Aboul Ella Hassanien
  • Ashraf Darwish
  • Hesham El-Askary
Series Title
Studies in Computational Intelligence
Series Volume
836
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-20212-5
DOI
10.1007/978-3-030-20212-5
Hardcover ISBN
978-3-030-20211-8
Softcover ISBN
978-3-030-20214-9
Series ISSN
1860-949X
Edition Number
1
Number of Pages
VIII, 232
Number of Illustrations
35 b/w illustrations, 62 illustrations in colour
Topics