Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms
- DOI
- 10.1016/j.envint.2022.107724
- Published
- 2023-01
- Container
- Environment International
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.envint.2022.107724,
title = {Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms},
author = {Fatemeh Rezaie and Mahdi Panahi and Sayed M. Bateni and Seonhong Kim and Jongchun Lee and Jungsub Lee and Juhee Yoo and Hyesu Kim and Sung Won Kim and Saro Lee},
year = {2023},
journal = {Environment International},
doi = {10.1016/j.envint.2022.107724},
url = {https://doi.org/10.1016/j.envint.2022.107724}
}RIS
TY - JOUR TI - Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms AU - Fatemeh Rezaie AU - Mahdi Panahi AU - Sayed M. Bateni AU - Seonhong Kim AU - Jongchun Lee AU - Jungsub Lee AU - Juhee Yoo AU - Hyesu Kim AU - Sung Won Kim AU - Saro Lee PY - 2023 JO - Environment International DO - 10.1016/j.envint.2022.107724 UR - https://doi.org/10.1016/j.envint.2022.107724 ER -
APA
Rezaie, F., Panahi, M., Bateni, S. M., Kim, S., Lee, J., Lee, J., Yoo, J., Kim, H., Kim, S. W., & Lee, S. (2023). Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms. Environment International. https://doi.org/10.1016/j.envint.2022.107724
Source records
- crossref · retrieved 2026-09-25T07:38:28.197Z