• AI-Optimised aeration control...

*Result*: AI-Optimised aeration control in SBR systems: an inverse SVM framework toward carbon-neutral wastewater treatment.

Title:
AI-Optimised aeration control in SBR systems: an inverse SVM framework toward carbon-neutral wastewater treatment.
Authors:
Cheng Q; Department of Material and Environmental Engineering, Chengdu Technological University, Chengdu, People's Republic of China.; Sichuan Provincial Engineering Research Center of Small and Medium Intelligent Wastewater Treatment Equipment, Chengdu, People's Republic of China., Yang Z; School of Architecture and Civil Engineering, Chengdu University, Chengdu, People's Republic of China., Guodong Y; Affiliated High School of University of Electronic Science and Technology of China, Chengdu, People's Republic of China., Ya L; Department of Material and Environmental Engineering, Chengdu Technological University, Chengdu, People's Republic of China., Le L; Power China Kunming Engineering Corporation Limited, Kunming, People's Republic of China., Xiuying W; Chengdu Yanji Intelligent Technology Co., Ltd, Chengdu, People's Republic of China., Juzhen W; Department of Material and Environmental Engineering, Chengdu Technological University, Chengdu, People's Republic of China., Mingxi W; School of Chemical and Environmental Engineering, Wuhan Institute of Technology, Wuhan, People's Republic of China., Qianglin L; Department of Material and Environmental Engineering, Chengdu Technological University, Chengdu, People's Republic of China.; Sichuan Provincial Engineering Research Center of Small and Medium Intelligent Wastewater Treatment Equipment, Chengdu, People's Republic of China.
Source:
Environmental technology [Environ Technol] 2026 Jan; Vol. 47 (1), pp. 37-51. Date of Electronic Publication: 2025 Oct 04.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Taylor & Francis Country of Publication: England NLM ID: 9884939 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1479-487X (Electronic) Linking ISSN: 09593330 NLM ISO Abbreviation: Environ Technol Subsets: MEDLINE
Imprint Name(s):
Publication: 2008- : Oxford : Taylor & Francis
Original Publication: London : Publications Division, Selper Ltd., 1990-
MeSH Terms:
Waste Disposal, Fluid*/methods , Wastewater* , Bioreactors* , Support Vector Machine*, Carbon
Contributed Indexing:
Keywords: Inverse support vector machine; aeration rate optimisation; artificial intelligence; sequencing batch reactor; wastewater treatment
Substance Nomenclature:
0 (Wastewater)
7440-44-0 (Carbon)
Entry Date(s):
Date Created: 20251004 Date Completed: 20251230 Latest Revision: 20251230
Update Code:
20260130
DOI:
10.1080/09593330.2025.2562373
PMID:
41045551
Database:
MEDLINE

*Further Information*

*This study proposes an inverse support vector machine (ISVM) framework to optimise aeration control in a sequencing batch reactor(SBR), addressing the balancing of energy efficiency and regulatory compliance in wastewater treatment. By integrating data-driven modelling with constrained optimisation, the method dynamically adjusts aeration rate to maintain effluent NH<subscript>3</subscript>-N concentrations below 5 mg/L while minimising energy consumption. A support vector machine (SVM) establishes input-output correlations between process parameters (influent NH<subscript>3</subscript>-N, ORP, conductivity, aeration rate) and effluent NH<subscript>3</subscript>-N concentration, enabling the ISVM to resolve constraint-driven aeration rate optimisation. Experimental validation across 20 operational cycles demonstrated a 20.3% reduction in energy usage compared to conventional fixed-rate aeration, achieving 95% compliance with discharge standards. The framework's penalty-based optimisation and gradient clipping mechanisms ensure stability in applications, overcoming limitations of traditional PID controllers and mechanistic models. This work advances intelligent control strategies for sustainable wastewater management, providing a constraint-aware optimisation template for environmental engineering systems.*