The Federal Aviation Administration is funding research into how neural networks, a form of artificial intelligence, might someday improve collision avoidance logic. These computational models mimic the layers of neurons in the human brain. The artificial versions are not nearly as complex as the brain, but they learn to solve problems efficiently through repeated exposure to data.


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    Titel :

    Solving the trust issue for neural nets


    Erschienen in:

    Aerospace America ; 55 , 6 ; 28


    Erscheinungsdatum :

    2017



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.88 Luftverkehr, Raumfahrt / 55.88
    Lokalklassifikation TIB:    770/7040



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    Solving the Infeasible Trust-Region Problem Using Approximations

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