Machine learning-based optimization strategy for comprehensive toxicity regulation in catalytic ozonation systems
- DOI
- 10.1016/j.watres.2026.127124
- Published
- 2027-01
- Container
- Water Research
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.watres.2026.127124,
title = {Machine learning-based optimization strategy for comprehensive toxicity regulation in catalytic ozonation systems},
author = {Jinglei Xu and Xianglin Chang and Shouqiang Wan and Aofan Wang and Beibei Yan and Ning Li and Guanyi Chen},
year = {2027},
journal = {Water Research},
doi = {10.1016/j.watres.2026.127124},
url = {https://doi.org/10.1016/j.watres.2026.127124}
}RIS
TY - JOUR TI - Machine learning-based optimization strategy for comprehensive toxicity regulation in catalytic ozonation systems AU - Jinglei Xu AU - Xianglin Chang AU - Shouqiang Wan AU - Aofan Wang AU - Beibei Yan AU - Ning Li AU - Guanyi Chen PY - 2027 JO - Water Research DO - 10.1016/j.watres.2026.127124 UR - https://doi.org/10.1016/j.watres.2026.127124 ER -
APA
Xu, J., Chang, X., Wan, S., Wang, A., Yan, B., Li, N., & Chen, G. (2027). Machine learning-based optimization strategy for comprehensive toxicity regulation in catalytic ozonation systems. Water Research. https://doi.org/10.1016/j.watres.2026.127124
Source records
- crossref · retrieved 2026-11-10T12:46:46.075Z