AIMC Topic: Wastewater

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Effective evaluation of greenhouse gases (GHGs) emissions from anoxic/oxic (A/O) process of regenerated papermaking wastewater treatment through hybrid deep learning techniques: Leveraging the critical role of water quality indicators.

Journal of environmental management Apr 1, 2025
Accurate accounting of greenhouse gases (GHGs) emissions from industrial wastewater treatment processes/plants with high organic concentration and fluctuating inflows is crucial for the calculation and management of carbon emissions. The impacts of w...
Deep Learning Waste Disposal, Fluid Neural Networks, Computer Wastewater Water Quality Greenhouse Gases
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Treatment options of nitrogen heterocyclic compounds in industrial wastewater: From fundamental technologies to energy valorization applications and future process design strategies.

Water research Mar 29, 2025
Nitrogen heterocyclic compounds (NHCs) widely exist in industrial wastewater and presented significant environmental and health risks due to their toxicity and persistence. This review addressed the challenges in treating NHCs in industrial wastewate...
Wastewater Water Purification Industrial Waste Heterocyclic Compounds Waste Disposal, Fluid Water Pollutants, Chemical
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Enhancing process monitoring and control in novel carbon capture and utilization biotechnology through artificial intelligence modeling: An advanced approach toward sustainable and carbon-neutral wastewater treatment.

Chemosphere Mar 17, 2025
Integrating carbon capture and utilization (CCU) technologies into wastewater treatment plants (WWTPs) is essential for mitigating greenhouse gas (GHG) emissions and enhancing environmental sustainability, but further advancements in process monitori...
Artificial Intelligence Wastewater Waste Disposal, Fluid Carbon Carbon Sequestration Carbon Dioxide Neural Networks, Computer Greenhouse Gases Biotechnology Photobioreactors
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Machine learning algorithms for predicting membrane bioreactors performance: A review.

Journal of environmental management Mar 17, 2025
Membrane bioreactors (MBR) are recognized as a sustainable technology for treating polluted effluents. Machine learning (ML) algorithms have emerged as a modeling option to predict pollutant removal and operational variables such as membrane fouling,...
Membranes, Artificial Wastewater Waste Disposal, Fluid Bioreactors Neural Networks, Computer Algorithms Machine Learning
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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...
Sewage Large Language Models Wastewater Water Purification 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...
Biological Oxygen Demand Analysis Salinity Nitrogen Hydrogen-Ion Concentration Carbon Bioreactors Machine Learning Wastewater Water Purification
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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 ...
Sample Size Sewage Algorithms Bacteria Machine Learning Wastewater
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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 Anaerobiosis Electrochemical Techniques Neural Networks, Computer Machine Learning Wastewater
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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...
Biofuels Machine Learning Wastewater Uncertainty Waste Disposal, Fluid
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