Dust Storm Attenuation Prediction Using a Hybrid Machine Learning Model Based on Measurements in Sudan

Dust Storm Attenuation Prediction Using a Hybrid Machine Learning Model Based on Measurements in Sudan

Sand and dust storms significantly challenge microwave and millimeter-wave communications, particularly in arid and semi-arid regions. Various models have been developed to predict attenuation caused by these storms theoretically and empirically based on two meteorological parameters, namely visibil...

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Bibliographic Details
Main Authors: Elfatih A. A. Elsheikh, E. I. Eltahir, Abdulkadir Tasdelen, Mosab Hamdan, Md Rafiqul Islam, Mohamed Hadi Habaebi, Aisha H. Abdullah Hashim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Dust storm attenuation
microwave propagation
meteorological parameters
terrestrial communication
machine learning
XGBoost
Online Access:https://ieeexplore.ieee.org/document/10843207/
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https://ieeexplore.ieee.org/document/10843207/

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