Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks. Sotiroudis, S., P., Goudos, S., K., & Siakavara, K. In 2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019, 2019. doi abstract bibtex 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.
@inproceedings{
title = {Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks},
type = {inproceedings},
year = {2019},
keywords = {artificial neural networks,path loss prediction,radio propagation,random forests},
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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.},
bibtype = {inproceedings},
author = {Sotiroudis, Sotirios P. and Goudos, Sotirios K. and Siakavara, Katherine},
doi = {10.1109/MOCAST.2019.8741751},
booktitle = {2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019}
}
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