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Ontologies as bayesian networks for ...

Vasilieva, Stephania.

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Ontologies as bayesian networks for space debris.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Ontologies as bayesian networks for space debris./
Author:	Vasilieva, Stephania.
Description:	65 p.
Notes:	Source: Masters Abstracts International, Volume: 55-05.
Contained By:	Masters Abstracts International55-05(E).
Subject:	Systems science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10119113
ISBN:	9781339804293

Ontologies as bayesian networks for space debris.
Vasilieva, Stephania.

Ontologies as bayesian networks for space debris. - 65 p.

Source: Masters Abstracts International, Volume: 55-05.

Thesis (M.S.)--The University of Arizona, 2016.

Space debris is a rising problem in today's world. Because there is so much in space that is unknown, it is critical to eventually catalog every piece. Since there are many attributes and properties attached to space objects, it is preferable to use an ontological classification method. The information presented in the ontology can then be used to answer questions about space debris. A Bayesian network would accomplish that because of its quantitative nature. The similarities between ontologies and Bayesian networks, such as their architectures and their flexibility, make it possible to integrate an ontology into a Bayesian network. Image determination and object collision assessment were used as applications to check the viability of integrating ontologies and Bayesian networks. It was determined that ontologies and Bayesian networks are tools that when combined can result in new useful quantitative information.

ISBN: 9781339804293Subjects--Topical Terms:

3168411
Systems science.

Ontologies as bayesian networks for space debris.
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020 $a 9781339804293
035 $a (MiAaPQ)AAI10119113
035 $a AAI10119113
040 $a MiAaPQ $c MiAaPQ
100 1 $a Vasilieva, Stephania. $3 3193964
245 1 0 $a Ontologies as bayesian networks for space debris.
300 $a 65 p.
500 $a Source: Masters Abstracts International, Volume: 55-05.
500 $a Adviser: Roberto Furfaro.
502 $a Thesis (M.S.)--The University of Arizona, 2016.
520 $a Space debris is a rising problem in today's world. Because there is so much in space that is unknown, it is critical to eventually catalog every piece. Since there are many attributes and properties attached to space objects, it is preferable to use an ontological classification method. The information presented in the ontology can then be used to answer questions about space debris. A Bayesian network would accomplish that because of its quantitative nature. The similarities between ontologies and Bayesian networks, such as their architectures and their flexibility, make it possible to integrate an ontology into a Bayesian network. Image determination and object collision assessment were used as applications to check the viability of integrating ontologies and Bayesian networks. It was determined that ontologies and Bayesian networks are tools that when combined can result in new useful quantitative information.
590 $a School code: 0009.
650 4 $a Systems science. $3 3168411
690 $a 0790
710 2 $a The University of Arizona. $b Systems Engineering. $3 3193965
773 0 $t Masters Abstracts International $g 55-05(E).
790 $a 0009
791 $a M.S.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10119113