AIMC Topic: Water Purification
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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...
Sustainable utilization of FeO-modified activated lignite for aqueous phosphate removal and ANN modeling.
Environmental research
Jul 14, 2024
Lignites are widely available and cost-effective in many countries. Sustainable methods for their utilization drive innovation, potentially advancing environmental sustainability and resource efficiency. In the present study, FeO (∼25.1 nm) supported...
Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model.
Water research
Jul 14, 2024
Owing to its simplicity of measurement, effluent conductivity is one of the most studied factors in evaluations of desalination performance based on the ion concentrations in various ion adsorption processes such as capacitive deionization (CDI) or b...
Prediction of hydroxyl radical exposure during ozonation using different machine learning methods with ozone decay kinetic parameters.
Water research
Jul 10, 2024
The abatement of micropollutants by ozonation can be accurately calculated by measuring the exposures of molecular ozone (O) and hydroxyl radical (OH) (i.e., ∫[O]dt and ∫[OH]dt). In the actual ozonation process, ∫[O]dt values can be calculated by mon...
Classification machine learning to detect de facto reuse and cyanobacteria at a drinking water intake.
The Science of the total environment
Jul 9, 2024
Harmful algal blooms (HABs) or higher levels of de facto water reuse (DFR) can increase the levels of certain contaminants at drinking water intakes. Therefore, the goal of this study was to use multi-class supervised machine learning (SML) classific...
Robust optimization of a novel ultraviolet (UV) photoreactor for water disinfection: A neural network approach.
Chemosphere
Jul 6, 2024
To optimize the ultraviolet (UV) water disinfection process, it is crucial to determine the ideal geometric dimensions of a corresponding model that enhance performance while minimizing the impact of uncertain photoreactor inputs. As water treatment ...
Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.
Environmental research
Jul 5, 2024
Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite mate...
Application of machine learning models to improve the prediction of pesticide photodegradation in water by ZnO-based photocatalysts.
Chemosphere
Jul 5, 2024
Pesticide pollution has been posing a significant risk to human and ecosystems, and photocatalysis is widely applied for the degradation of pesticides. Machine learning (ML) emerges as a powerful method for modeling complex water treatment processes....
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...
Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose.
Environmental geochemistry and health
Jun 26, 2024
This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characteriza...
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