AIMC Topic: Wastewater

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Multi-agent large language model frameworks: Unlocking new possibilities for optimizing wastewater treatment operation.

Environmental research Mar 14, 2025
Wastewater treatment plants (WWTPs) are highly complex systems where biological, chemical, and physical processes interact dynamically, creating significant operational challenges. Traditional modeling approaches, such as Activated Sludge Models (ASM...
Wastewater Water Purification Sewage Large Language Models Waste Disposal, Fluid Models, Theoretical
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Enhanced nitrogen prediction and mechanistic process analysis in high-salinity wastewater treatment using interpretable machine learning approach.

Bioresource technology Mar 11, 2025
This study introduces an interpretable machine learning framework to predict nitrogen removal in membrane bioreactor (MBR) treating high-salinity wastewater. By integrating Shapley additive explanations (SHAP) with Categorical Boosting (CatBoost), we...
Water Purification Carbon Machine Learning Wastewater Hydrogen-Ion Concentration Biological Oxygen Demand Analysis Bioreactors Nitrogen Salinity
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Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.

Journal of environmental management Mar 9, 2025
Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associated with traditional detection methods. In recent years, researchers capitalized on this potential ...
Algorithms Machine Learning Bacteria Wastewater Sample Size Sewage
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Application of Machine Learning for FOS/TAC Soft Sensing in Bio-Electrochemical Anaerobic Digestion.

Molecules (Basel, Switzerland) Feb 27, 2025
This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating bre...
Support Vector Machine Electrochemical Techniques Neural Networks, Computer Wastewater Anaerobiosis Machine Learning
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Machine learning in wastewater: opportunities and challenges - "not everything is a nail!".

Current opinion in biotechnology Feb 24, 2025
This paper highlights the potential of machine learning (ML) for wastewater applications, with a focus on key applications and considerations. It underscores the need for simplicity in ML models to ensure their interpretability and trustworthiness, c...
Machine Learning Wastewater
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A machine learning approach to feature selection and uncertainty analysis for biogas production in wastewater treatment plants.

Waste management (New York, N.Y.) Feb 21, 2025
The growing demand for efficient waste management solutions and renewable energy sources has driven research into predicting biogas production at wastewater treatment plants. This study outlines a methodology starting with data collection from a full...
Wastewater Waste Disposal, Fluid Uncertainty Machine Learning Biofuels
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Carbon source dosage intelligent determination using a multi-feature sensitive back propagation neural network model.

Journal of environmental management Feb 15, 2025
The carbon reduction concept drives the development of low-carbon and sustainable wastewater treatment plant (WWTP) operation technologies. In the denitrification stage of WWTPs in China, there are widespread problems of uneconomical dosage consumpti...
China Waste Disposal, Fluid Carbon Nitrogen Machine Learning Wastewater Neural Networks, Computer
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Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural Network.

Environmental science & technology Feb 12, 2025
Deciphering and mitigating dynamic greenhouse gas (GHG) emissions under environmental fluctuation in urban drainage systems (UDGSs) is challenging due to the absence of a high-prediction model that accurately quantifies the contributions of biologica...
Wastewater Methane Greenhouse Gases Nitrous Oxide Neural Networks, Computer Graph Neural Networks
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Bayesian Optimization-Enhanced Reinforcement learning for Self-adaptive and multi-objective control of wastewater treatment.

Bioresource technology Feb 9, 2025
Controllers of wastewater treatment plants (WWTPs) often struggle to maintain optimal performance due to dynamic influent characteristics and the need to balance multiple operational objectives. In this study, Reinforcement Learning (RL) algorithms a...
Water Purification Bayes Theorem Waste Disposal, Fluid Sewage Wastewater Machine Learning Algorithms
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Application of machine learning for environmentally friendly advancement: exploring biomass-derived materials in wastewater treatment and agricultural sector - a review.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Feb 2, 2025
There are several uses for biomass-derived materials (BDMs) in the irrigation and farming industries. To solve problems with material, process, and supply chain design, BDM systems have started to use machine learning (ML), a new technique approach. ...
Agriculture Waste Disposal, Fluid Wastewater Machine Learning Biomass
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