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- W3126906721 abstract "AbstractRain attenuation is an important factor affecting wireless communication systems throughout the world. Rain attenuation and rain rate data are collected using multichannel radiometer and laser precipitation monitor at a tropical location. The dataset obtained is used to initially propose an empirical model for prediction of rain attenuation from rain rate data. An alternative model using linear spline regression-based machine learning is also used to predict rain attenuation. The machine learning-based model is found to be more accurate by an appreciable degree compared to the empirical model proposed in the previous instance. KeywordsRain attenuationMultichannel radiometerEmpirical modelLinear splineRegressionMachine learning" @default.
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- W3126906721 date "2021-01-01" @default.
- W3126906721 modified "2023-09-24" @default.
- W3126906721 title "Machine Learning-Based Rain Attenuation Prediction Model" @default.
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- W3126906721 doi "https://doi.org/10.1007/978-981-15-8366-7_3" @default.
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