In this paper, neural network (NN) modeling is combined with fuzzy logic to estimate Interference Path Loss measurements on Airbus 319 and 320 airplanes. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structures and the communication/navigation system-of-concern. Modeled results are compared with measured data. Combining fuzzy logic and NN modeling is shown to improve estimates of measured data over estimates obtained with NN alone. A plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft.


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    Title :

    Interference Path Loss Prediction in A319/320 Airplanes Using Modulated Fuzzy Logic and Neural Networks


    Contributors:

    Conference:

    NAFIPS 2007: North American Fuzzy Information Processing Society ; 2007 ; San Diego, CA, United States


    Publication date :

    2007-06-24


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English