The applicability of neural networks to ionospheric modeling in support of relocatable over-the-horizon radar
Pinkepank, James Alan
Collins, Daniel Joseph
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Ionospheric models have been developed to interpret Relocatable Over-the-Horizon Radar data. This thesis examines the applicability of neural networks to ionospheric modeling in support of Relocatable Over-the-Horizon Radar. Two neural networks were used for this investigation. The flrst network was trained and tested on experimental ionospheric sounding data. Results showed neural networks are excellent at modeling ionospheric data for a given day. The second network was trained on ionospheric models and tested on experimental data. Results showed neural networks are able to learn many ionospheric models and the modeling network generally agreed with the experimental data.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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