國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Machine learning and data mining in ...

Darwish, Ashraf.

Machine learning and data mining in aerospace technology

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning and data mining in aerospace technologyedited by Aboul Ella Hassanien, Ashraf Darwish, Hesham El-Askary.
其他作者:	Hassanien, Aboul Ella.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	viii, 232 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machine learning.
電子資源:	https://doi.org/10.1007/978-3-030-20212-5
ISBN:	9783030202125$q(electronic bk.)

Machine learning and data mining in aerospace technology
Machine learning and data mining in aerospace technology[electronic resource] /edited by Aboul Ella Hassanien, Ashraf Darwish, Hesham El-Askary. - Cham :Springer International Publishing :2020. - viii, 232 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8361860-949X ;. - Studies in computational intelligence ;v. 216..

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.

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.

ISBN: 9783030202125$q(electronic bk.)

Standard No.: 10.1007/978-3-030-20212-5doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .M33 2020

Dewey Class. No.: 006.31

Machine learning and data mining in aerospace technology
LDR:03198nmm a2200337 a 4500 001 593217
003 DE-He213
005 20200703082218.0
006 m d
007 cr nn 008maaau
008 210727s2020 sz s 0 eng d
020 $a 9783030202125$q(electronic bk.)
020 $a 9783030202118$q(paper)
024 7 $a 10.1007/978-3-030-20212-5 $2 doi
035 $a 978-3-030-20212-5
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .M33 2020
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M149 2020
245 0 0 $a Machine learning and data mining in aerospace technology $h [electronic resource] / $c edited by Aboul Ella Hassanien, Ashraf Darwish, Hesham El-Askary.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a viii, 232 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.836
505 0 $a 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.
520 $a 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.
650 0 $a Machine learning. $3 188639
650 0 $a Data mining. $3 184440
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Aerospace Technology and Astronautics. $3 309707
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Hassanien, Aboul Ella. $3 266212
700 1 $a Darwish, Ashraf. $3 884502
700 1 $a El-Askary, Hesham. $3 884503
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 216. $3 380871
856 4 0 $u https://doi.org/10.1007/978-3-030-20212-5
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)