Name
Title | ||
|---|---|---|
Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks |
Abstract | ||
|---|---|---|
The prediction of propagation path loss is of great importance for all aspects of mobile communication. Machine learning methods, such as Artificial Neural Networks and Random Forests, can play a key role for its estimation. A comparison between the two methods for the frequencies of 900 MHz and 1800 MHz is being carried out in the work at hand. Both methods led to similar results. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MOCAST.2019.8741751 | 2019 8th International Conference on Modern Circuits and Systems Technologies (MOCAST) |
Keywords | Field | DocType |
artificial neural networks,random forests,path loss prediction,radio propagation | Computer science,Internet of Things,Path loss,Random forest,Artificial neural network,Radio propagation,Mobile telephony,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-7281-1185-8 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sotirios P. Sotiroudis | 1 | 0 | 0.34 |
| S. K. Goudos | 2 | 6 | 2.73 |
| K. Siakavara | 3 | 6 | 3.87 |