AIMC Topic: Wastewater
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Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.
Environmental monitoring and assessment
Feb 1, 2025
Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on...
Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment.
Journal of environmental management
Jan 31, 2025
Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improving treatment performance. Supervised deep learning methods show high performance to automatically detect particles, but they rely on vast amounts of l...
Design optimization and predictive modeling for TSS in mega surface WWTPs: A machine learning approach.
Journal of environmental management
Jan 29, 2025
Surface wastewater originates from various sources, including domestic, commercial, and industrial activities, and contains a mix of organic and inorganic wastes along with suspended and dissolved solids that require effective treatment. This study p...
Predicting biomass conversion and COD removal in wastewater treatment by phototrophic bacteria with interpretable machine learning.
Journal of environmental management
Jan 24, 2025
Photosynthetic bacteria (PSB) excel in wastewater treatment by removing pollutants and generating biomass but are challenging to optimize due to complex operational and environmental interactions. Neural Ordinary Differential Equations, Elastic Net, ...
Attention-based deep learning models for predicting anomalous shock of wastewater treatment plants.
Water research
Jan 23, 2025
Quickly grasping the time-consuming water quality indicators (WQIs) such as total nitrogen (TN) and total phosphorus (TP) of influent is an essential prerequisite for wastewater treatment plants (WWTPs) to prompt respond to sudden shock loads. Soft d...
Using machine learning models to predict the dose-effect curve of municipal wastewater for zebrafish embryo toxicity.
Journal of hazardous materials
Jan 20, 2025
Municipal wastewater substantially contributes to aquatic ecological risks. Assessing the toxicity of municipal wastewater through dose-effect curves is challenging owing to the time-consuming, labor-intensive, and costly nature of biological assays....
Optimizing papermaking wastewater treatment by predicting effluent quality with node-level capsule graph neural networks.
Environmental monitoring and assessment
Jan 18, 2025
Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is crucial. Because wastewater treatment processes are complicated, nonlinear, and time-varying, it is e...
Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning.
Nano letters
Jan 17, 2025
Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for bacterial diseases. This is in part owing to difficulties in distinguishing pathogenic from nonpatho...
Application of supervised learning models for enhanced lead (II) removal from wastewater via modified cellulose nanocrystals (CNCs).
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jan 16, 2025
Heavy metal ions are acknowledged to impact the environment and human health adversely. CNCs are effective materials for removing heavy metal ions in industrial applications and process innovations since they can be used in static and dynamic adsorpt...
Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.
Viruses
Jan 15, 2025
Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and res...
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