To understand the characteristics of aircraft stall for better aerodynamic model, the physical essence of the stall phenomena of aircraft is first introduced, and then a Wavelet Neural Network (WNN) is proposed to set up the stall aerodynamic model. Numerical examples indicates that through the deep cognition of the stall phenomena of aircraft the proposed stall aerodynamic method has a better accuracy than the traditional neural network and is also effective and feasible.


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    Titel :

    Physical Essence of Stall Phenomena and its WNN-Based Aerodynamic Modeling from Flight Data



    Erschienen in:

    Applied Mechanics and Materials ; 602-605 ; 3140-3143


    Erscheinungsdatum :

    2014-08-11


    Format / Umfang :

    4 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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