Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks
- DOI
- 10.3390/drones7120701
- Published
- 12
- Container
- Drones
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/drones7120701,
title = {Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks},
author = {Hanpeng Li and Kai Mao and Xuchao Ye and Taotao Zhang and Qiuming Zhu and Manxi Wang and Yurao Ge and Hangang Li and Farman Ali},
year = {2023},
journal = {Drones},
doi = {10.3390/drones7120701},
url = {https://doi.org/10.3390/drones7120701}
}RIS
TY - JOUR TI - Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks AU - Hanpeng Li AU - Kai Mao AU - Xuchao Ye AU - Taotao Zhang AU - Qiuming Zhu AU - Manxi Wang AU - Yurao Ge AU - Hangang Li AU - Farman Ali PY - 2023 JO - Drones DO - 10.3390/drones7120701 UR - https://doi.org/10.3390/drones7120701 ER -
APA
Li, H., Mao, K., Ye, X., Zhang, T., Zhu, Q., Wang, M., Ge, Y., Li, H., & Ali, F. (2023). Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks. Drones. https://doi.org/10.3390/drones7120701
Source records
- doaj · retrieved 2026-09-25T03:37:52.948Z