AIMC Topic: Wastewater
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Validity of zinc oxide nanoparticles biosynthesized in food wastes extract in treating real samples of printing ink wastewater; prediction models using feed-forward neural network (FFNN).
Chemosphere
Jul 5, 2024
In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samples of printing ink wastewater. FWEZnO NPs were prepared using green synthesis methods using a compo...
Development of an artificial neural network (ANN) for the prediction of a pilot scale mobile wastewater treatment plant performance.
Journal of environmental management
Jul 5, 2024
Productive activities such as pig farming are a fundamental part of the economy in Mexico. Unfortunately, because of this activity, large quantities of wastewater are generated that have a negative impact in the environment. This work shows an altern...
Online soft measurement method for chemical oxygen demand based on CNN-BiLSTM-Attention algorithm.
PloS one
Jun 28, 2024
The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and la...
Machine Learning-Assisted Optimization of Mixed Carbon Source Compositions for High-Performance Denitrification.
Environmental science & technology
Jun 20, 2024
Appropriate mixed carbon sources have great potential to enhance denitrification efficiency and reduce operational costs in municipal wastewater treatment plants (WWTPs). However, traditional methods struggle to efficiently select the optimal mixture...
Machine learning screening of biomass precursors to prepare biomass carbon for organic wastewater purification: A review.
Chemosphere
Jun 16, 2024
In the past decades, the amount of biomass waste has continuously increased in human living environments, and it has attracted more and more attention. Biomass is regarded as the most high-quality and cost-effective precursor material for the prepara...
Prediction of COD in industrial wastewater treatment plant using an artificial neural network.
Scientific reports
Jun 14, 2024
In this investigation, the modeling of the Aksaray industrial wastewater treatment plant was performed using artificial neural networks with various architectures in the MATLAB software. The dataset utilized in this study was collected from the Aksar...
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 ...
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