Machine Learning and Data Mining in Aerospace Technology
Author | : Aboul Ella Hassanien |
Publisher | : Springer |
Total Pages | : 236 |
Release | : 2019-07-02 |
ISBN-13 | : 9783030202125 |
ISBN-10 | : 3030202127 |
Rating | : 4/5 (27 Downloads) |
Download or read book Machine Learning and Data Mining in Aerospace Technology written by Aboul Ella Hassanien and published by Springer. This book was released on 2019-07-02 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.