The process of technological gentrification can be seen in various areas of aerospace engineering with the help of accumulated data. The collected data of aerial vehicles can be used for generating status of maneuvering that affects the trajectories of designated journey. Leveraging predictive analytics using deep learning can certainly automate the task of flight maneuvering. This research study implements various deep learning techniques to predict the maneuver status from the aerial vehicle accumulated data. The proposed research study is heavily result oriented and includes a complete process of network advancement to tackle every problem to reach the best possible metrics.


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    Titel :

    Implementing Deep Learning Techniques for Trajectories of Flights to Yield Maneuver Status


    Beteiligte:
    Mhatre, Sakshi (Autor:in) / Nair, Amrita (Autor:in) / Kadam, Prachi (Autor:in) / Joshi, Raunak (Autor:in)


    Erscheinungsdatum :

    2023-11-22


    Format / Umfang :

    330604 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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