AIMC Topic: Water Purification
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Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives.
Bioresource technology
May 18, 2024
Developing an optimized and targeted design approach for metal-modified biochar based on water quality conditions and management is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate a...
Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Apr 12, 2024
Heavy metal ions are considered to be the most prevalent and toxic water contaminants. The objective of thois work was to investigate the effectiveness of employing the adsorption technique in a laboratory-size reactor to remove copper (II) ions from...
Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities.
Chemosphere
Apr 10, 2024
In water treatment processes (WTPs), artificial intelligence (AI) based techniques, particularly machine learning (ML) models have been increasingly applied in decision-making activities, process control and optimization, and cost management. At leas...
Investigation of direct contact membrane distillation (DCMD) performance using CFD and machine learning approaches.
Chemosphere
Apr 9, 2024
Direct Contact Membrane Distillation (DCMD) is emerging as an effective method for water desalination, known for its efficiency and adaptability. This study delves into the performance of DCMD by integrating two powerful analytical tools: Computation...
Amino-functionalized novel biosorbent for effective removal of fluoride from water: process optimization using artificial neural network and mechanistic insights.
Environmental science and pollution research international
Apr 5, 2024
Aqueous fluoride ( ) pollution is a global threat to potable water security. The present research envisions the development of novel adsorbents from indigenous Limonia acidissima L. (fruit pericarp) for effective aqueous defluoridation. The adsorben...
Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.
Water research
Apr 1, 2024
Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR ...
Solar desalination system for fresh water production performance estimation in net-zero energy consumption building: A comparative study on various machine learning models.
Water science and technology : a journal of the International Association on Water Pollution Research
Mar 20, 2024
This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as ...
Genetic programming expressions for effluent quality prediction: Towards AI-driven monitoring and management of wastewater treatment plants.
Journal of environmental management
Mar 14, 2024
Continuous effluent quality prediction in wastewater treatment processes is crucial to proactively reduce the risks to the environment and human health. However, wastewater treatment is an extremely complex process controlled by several uncertain, in...
A comprehensive review on artificial intelligence in water treatment for optimization. Clean water now and the future.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jan 31, 2024
Given the severe effects that toxic compounds present in wastewater streams have on humans, it is imperative that water and wastewater streams pollution be addressed globally. This review comprehensively examines various water and wastewater treatmen...
A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant.
Water research
Dec 30, 2023
Wastewater treatment plant (WWTP) operation is usually intricate due to large variations in influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTP effluent water quality can provide valuable decision-making supp...
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