Advanced physics-enhanced machine learning and empirical approaches for estimating the oxygen transfer alpha factor in activated sludge.
- DOI
- 10.1016/j.biortech.2026.135661
- Published
- 2026 Aug 17
- Container
- Bioresource technology
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.biortech.2026.135661,
title = {Advanced physics-enhanced machine learning and empirical approaches for estimating the oxygen transfer alpha factor in activated sludge.},
author = {Shadkani S and Fisk AT and Saber A},
year = {2026},
journal = {Bioresource technology},
doi = {10.1016/j.biortech.2026.135661},
url = {https://doi.org/10.1016/j.biortech.2026.135661}
}RIS
TY - JOUR TI - Advanced physics-enhanced machine learning and empirical approaches for estimating the oxygen transfer alpha factor in activated sludge. AU - Shadkani S AU - Fisk AT AU - Saber A PY - 2026 JO - Bioresource technology DO - 10.1016/j.biortech.2026.135661 UR - https://doi.org/10.1016/j.biortech.2026.135661 ER -
APA
S, S., AT, F., & A, S. (2026). Advanced physics-enhanced machine learning and empirical approaches for estimating the oxygen transfer alpha factor in activated sludge.. Bioresource technology. https://doi.org/10.1016/j.biortech.2026.135661
Source records
- pubmed · retrieved 2026-09-26T14:29:29.478Z