Text mining and machine learning based health risk prediction for soil polycyclic aromatic hydrocarbons at typical coal-fired industrial sites in china
- DOI
- 10.1016/j.jhazmat.2026.141934
- Published
- 2026-05
- Container
- Journal of Hazardous Materials
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jhazmat.2026.141934,
title = {Text mining and machine learning based health risk prediction for soil polycyclic aromatic hydrocarbons at typical coal-fired industrial sites in china},
author = {Lu Han and Hanyuan Gu and Mengfang Chen and Zhanfei He and Yufei Jia and Yudong Feng and Jing Li and Ya Zhu and Ye zou},
year = {2026},
journal = {Journal of Hazardous Materials},
doi = {10.1016/j.jhazmat.2026.141934},
url = {https://doi.org/10.1016/j.jhazmat.2026.141934}
}RIS
TY - JOUR TI - Text mining and machine learning based health risk prediction for soil polycyclic aromatic hydrocarbons at typical coal-fired industrial sites in china AU - Lu Han AU - Hanyuan Gu AU - Mengfang Chen AU - Zhanfei He AU - Yufei Jia AU - Yudong Feng AU - Jing Li AU - Ya Zhu AU - Ye zou PY - 2026 JO - Journal of Hazardous Materials DO - 10.1016/j.jhazmat.2026.141934 UR - https://doi.org/10.1016/j.jhazmat.2026.141934 ER -
APA
Han, L., Gu, H., Chen, M., He, Z., Jia, Y., Feng, Y., Li, J., Zhu, Y., & zou, Y. (2026). Text mining and machine learning based health risk prediction for soil polycyclic aromatic hydrocarbons at typical coal-fired industrial sites in china. Journal of Hazardous Materials. https://doi.org/10.1016/j.jhazmat.2026.141934
Source records
- crossref · retrieved 2026-09-26T08:18:53.393Z