AIMC Topic: Wastewater
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Learning a neural network-based soft sensor with double-errors parallel optimization towards effluent variable prediction in wastewater treatment plants.
Journal of environmental management
Jul 24, 2024
With the development of machine learning and artificial intelligence (ML/AI) models, data-driven soft sensors, especially the neural network-based, have widespread utilization for the prediction of key water quality indicators in wastewater treatment...
Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective.
Chemosphere
Jul 15, 2024
The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN...
Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches.
The Science of the total environment
Jul 11, 2024
Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (TPs) is very limited. Here, we investigated occurrence and transformation of pharmaceuticals and TPs...
Optimization of a Novel Engineered Ecosystem Integrating Carbon, Nitrogen, Phosphorus, and Sulfur Biotransformation for Saline Wastewater Treatment Using an Interpretable Machine Learning Approach.
Environmental science & technology
Jul 10, 2024
The denitrifying sulfur (S) conversion-associated enhanced biological phosphorus removal (DS-EBPR) process for treating saline wastewater is characterized by its unique microbial ecology that integrates carbon (C), nitrogen (N), phosphorus (P), and S...
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...
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