Comparative analysis of major machine-learning-based path loss models for enclosed indoor channels

HIGHLIGHTS

• who: Mohamed K. Elmezughi and colleagues from the The Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal have published the Article: Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels, in the Journal: Sensors 2022, 22, 4967. of 13/04/2022
• what: The main results obtained from this study show that the best root-mean-square error (RMSE) performance is given by the ANN and RNN-LSTM methods while the worst is for the MLR method. This work shows that the models (except for the MLR model . . .
  

   

  

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