Machine Learning and Data Mining in Aerospace Technology

Author:   Aboul Ella Hassanien ,  Ashraf Darwish ,  Hesham El-Askary
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   836
ISBN:  

9783030202118


Pages:   232
Publication Date:   16 July 2019
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Machine Learning and Data Mining in Aerospace Technology


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Author:   Aboul Ella Hassanien ,  Ashraf Darwish ,  Hesham El-Askary
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   836
Weight:   0.530kg
ISBN:  

9783030202118


ISBN 10:   3030202119
Pages:   232
Publication Date:   16 July 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Tensor-based anomaly detection for satellite telemetry data.- Machine learning in satellites monitoring and risk challenges.- Formalization, prediction and recognition of expert evaluations of telemetric data of artificial satellites based on type-II fuzzy sets.- Intelligent health monitoring systems for space missions based on data mining techniques.- Design, implementation, and validation of satellite simulator and data packets analysis.- Crop yield estimation using decision trees and random forest machine learning algorithms on data from terra (EOS AM-1) & aqua (EOS PM-1) satellite data.- Data analytics using satellite remote sensing in healthcare applications.- Design, Implementation, and Testing of Unpacking System for Telemetry Data of Artificial Satellites: Case Study: EGYSAT1.- Multiscale Satellite Image Classification using Deep Learning Approach.- Security approaches in machine learning for satellite communication.- Machine learning techniques for IoT intrusions detection in aerospace cyber physical systems.

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