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    Ontologies as Bayesian Networks for Space Debris

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    Author
    Vasilieva, Stephania
    Issue Date
    2016
    Keywords
    Systems Engineering
    Advisor
    Furfaro, Roberto
    
    Metadata
    Show full item record
    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
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Graduate College
    Systems Engineering
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

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