Persistent Link:
http://hdl.handle.net/10150/613564
Title:
Ontologies as Bayesian Networks for Space Debris
Author:
Vasilieva, Stephania
Issue Date:
2016
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
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.
Type:
text; Electronic Thesis
Keywords:
Systems Engineering
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Systems Engineering
Degree Grantor:
University of Arizona
Advisor:
Furfaro, Roberto

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleOntologies as Bayesian Networks for Space Debrisen_US
dc.creatorVasilieva, Stephaniaen
dc.contributor.authorVasilieva, Stephaniaen
dc.date.issued2016-
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.description.abstractSpace 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.en
dc.typetexten
dc.typeElectronic Thesisen
dc.subjectSystems Engineeringen
thesis.degree.nameM.S.en
thesis.degree.levelmastersen
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineSystems Engineeringen
thesis.degree.grantorUniversity of Arizonaen
dc.contributor.advisorFurfaro, Robertoen
dc.contributor.committeememberLepore, Roberten
dc.contributor.committeememberHead, Larry K.en
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