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What is Machine Learning for Path Loss Prediction about?

This paper evaluates various machine learning methods for predicting path loss in rural environments at 3.7 GHz, utilizing models such as ANN, SVR, RF, and B-kNN. The results indicate that all machine learning models outperform traditional empirical models, with the best performance achieved by a three-hidden-layer ANN yielding an RMSE of 4.0 dB. The study highlights the effectiveness of machine learning techniques in enhancing path loss predictions in rural settings, marking a significant advancement in wi

Author

goosetable

Language

EN