| Title: |
Modeling of a mainstream partial nitrification/anammox process through a hybrid theoretical-machine learning approach |
| Authors: |
Alvarado, V; Ying, L; Asghari, V; Hsu, SC; Lee, PH |
| Contributors: |
Department of Civil and Environmental Engineering |
| Publisher Information: |
American Chemical Society |
| Publication Year: |
2026 |
| Collection: |
Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR) |
| Subject Terms: |
Anammox; Fluidized bed membrane bioreactor; Microbial interactions; Partial nitritation; Theoretical-machine learning; Wastewater treatment |
| Description: |
202601 bcch ; Accepted Manuscript ; RGC ; Others ; The authors thank the Hong Kong Research Grants Council- University Grants Committee (Grant No. 15252916 and UGC/GEN/456/08), and the Research Institute for Sustainable Urban Development (RISUD) for their financial support. Declarations of interest: none. ; Published ; Green (AAM) |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://hdl.handle.net/10397/117017; 1469; 1480 |
| DOI: |
10.1021/acsestwater.4c01220 |
| Availability: |
https://hdl.handle.net/10397/117017; https://doi.org/10.1021/acsestwater.4c01220 |
| Rights: |
© 2025 American Chemical Society ; This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS ES&T Water, copyright © 2025 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsestwater.4c01220. |
| Accession Number: |
edsbas.9388598F |
| Database: |
BASE |