Abstract
A generalised regression neural network is used to predict losses inherent in ionospheric radiowave propagation. Network inputs consist of sun declination, time of day, radio flux, geomagnetic A-index and X-ray flux. Simulations for a 400 km path demonstrate a 2.5 dB error between network predictions and actual measured values, representing a 46% reduction in errors compared to the linear regression method.
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