In this paper, we propose a new modeling method for improving accuracy of weapon launch acceptability region. To enhance the model accuracy and memory requirements, the proposed method is based on training technique using wavelet neural network. The accuracy relative to the truth data set, which consists of grid data, generated using the weapon 6 degree of freedom simulation is evaluated. In the experiment results, true/false coverage area statistics show about 3.42% and 2.86% improvement compared to the conventional modeling method. Also, the memory requirements lead to about a 60% reduction on average.


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    Titel :

    New modeling algorithm for improving accuracy of weapon launch acceptability region


    Beteiligte:
    Kun Su Yoon, (Autor:in) / Jae Hyun Park, (Autor:in) / In Gyu Kim, (Autor:in) / Kwang Su Ryu, (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.10.2010


    Format / Umfang :

    316785 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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