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Implementation of Artificial Neural Network for Prediction of Rain Attenuation in Microwave and Millimeter Wave Frequencies

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Author(s): Amarjit | Gangwar R.P.S

Journal: IETE Journal of Research
ISSN 0377-2063

Volume: 54;
Issue: 5;
Start page: 346;
Date: 2008;
Original page

Keywords: Artificial neural network | Extinction cross section | Finite element method | Rain attenuation | Raindrop models.

ABSTRACT
The artificial neural network model is developed on the extinction cross section data derived from the modified Pruppacher-and-Pitter (MPP) raindrop model, using finite element method (FEM) in microwave and millimeter wave frequencies ranging from 1 to 100 GHz, with mean raindrop radii from 0.025 to 0.35 cm for horizontal and vertical polarizations. The mean square error and correlation coefficient R 2 values between derived data using FEM on MPP raindrop and artificial neural network (ANN) are found to be 1.62 x 10−4 and 0.9994 for vertical polarization, and 4.677 x 10−3 and 0.9943 for horizontal polarization. The artificial neural network model gives results with good accuracy for calculating extinction cross section of raindrop. It is then applied on raindrop size distributions of Singapore and the Indian regions, for the prediction of specific rain attenuation. The results of specific rain attenuation obtained using ANN are compared with reported experimental data and they are found to be in close agreement.
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