AIMC Topic: Wastewater
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Wastewater treatment process enhancement based on multi-objective optimization and interpretable machine learning.
Journal of environmental management
Jun 13, 2024
Optimization and control of wastewater treatment process (WTP) can contribute to cost reduction and efficiency. A wastewater treatment process multi-objective optimization (WTPMO) framework is proposed in this paper to provide suggestions for decisio...
Deep learning-based flocculation sensor for automatic control of flocculant dose in sludge dewatering processes during wastewater treatment.
Water research
Jun 6, 2024
In sludge dewatering of most wastewater treatment plants (WWTPs), the dose of polymer flocculant is manually adjusted through direct visual inspection of the flocs without the aid of any instruments. Although there is a demand for the development of ...
Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques.
Chemosphere
Jun 4, 2024
The two main things needed to fulfill the world's impending need for water in the face of the widespread water crisis are collecting water and recycling. To do this, the present study has placed a greater focus on water management strategies used in ...
Predicting the Occurrence of Substituted and Unsubstituted, Polycyclic Aromatic Compounds in Coking Wastewater Treatment Plant Effluent using Machine Learning Regression.
Chemosphere
May 28, 2024
Organic contaminants such as polycyclic aromatic compounds (PACs) occurring in industrial effluents can not only persist in wastewater but transform into more toxic and mobile, substituted heterocyclic products during treatment. Thus, predicting the ...
Enhanced wastewater treatment by catalytic persulfate activation with protonated hydroxylamine-assisted iron: Insights from a deep learning-based numerical investigation.
Chemosphere
May 25, 2024
Machine learning-enhanced molecular network reveals global exposure to hundreds of unknown PFAS.
Science advances
May 23, 2024
Unknown forever chemicals like per- and polyfluoroalkyl substances (PFASs) are difficult to identify. Current platforms designed for metabolites and natural products cannot capture the diverse structural characteristics of PFAS. Here, we report an au...
Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.
The Science of the total environment
May 3, 2024
Chemical and pharmaceutical chemicals found in water sources create substantial risks to human health and the environment. The presence of pharmaceutical contaminants in water can cause antibiotic resistance development, toxicity to aquatic organisms...
Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios.
Water research
May 2, 2024
Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV...
Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.
Chemosphere
May 2, 2024
Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept...
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