Rapid identification of hazardous waste from the steel industry based on machine learning-driven infrared spectroscopy
- DOI
- 10.1016/j.wasman.2026.115978
- Published
- 2027-01
- Container
- Waste Management
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.wasman.2026.115978,
title = {Rapid identification of hazardous waste from the steel industry based on machine learning-driven infrared spectroscopy},
author = {Guanyi Chen and Sen Yang and Rui Liang and Zaixin Li and Chang Ma and Beibei Yan and Zhanjun Cheng and Junyu Tao},
year = {2027},
journal = {Waste Management},
doi = {10.1016/j.wasman.2026.115978},
url = {https://doi.org/10.1016/j.wasman.2026.115978}
}RIS
TY - JOUR TI - Rapid identification of hazardous waste from the steel industry based on machine learning-driven infrared spectroscopy AU - Guanyi Chen AU - Sen Yang AU - Rui Liang AU - Zaixin Li AU - Chang Ma AU - Beibei Yan AU - Zhanjun Cheng AU - Junyu Tao PY - 2027 JO - Waste Management DO - 10.1016/j.wasman.2026.115978 UR - https://doi.org/10.1016/j.wasman.2026.115978 ER -
APA
Chen, G., Yang, S., Liang, R., Li, Z., Ma, C., Yan, B., Cheng, Z., & Tao, J. (2027). Rapid identification of hazardous waste from the steel industry based on machine learning-driven infrared spectroscopy. Waste Management. https://doi.org/10.1016/j.wasman.2026.115978
Source records
- crossref · retrieved 2026-11-07T16:33:46.058Z