AIMC Topic: Wastewater

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Predicting the concentration of total coliforms in treated rural domestic wastewater by multi-soil-layering (MSL) technology using artificial neural networks.

Ecotoxicology and environmental safety Aug 11, 2020
Many indicators are involved in monitoring water quality. For instance, the fecal indicator bacteria are extremely important to detect the water quality. For this purpose, to better predict the total coliforms at the outlet of a Multi-Soil-Layering (...
Neural Networks, Computer Wastewater Water Quality Water Microbiology Morocco Soil Bacteria Environmental Monitoring
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An integrated approach based on virtual data augmentation and deep neural networks modeling for VFA production prediction in anaerobic fermentation process.

Water research Jun 30, 2020
Data-driven models are suitable for simulating biological wastewater treatment processes with complex intrinsic mechanisms. However, raw data collected in the early stage of biological experiments are normally not enough to train data-driven models. ...
Fermentation Wastewater Anaerobiosis Fatty Acids, Volatile Neural Networks, Computer
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Learning soft sensors using time difference-based multi-kernel relevance vector machine with applications for quality-relevant monitoring in wastewater treatment.

Environmental science and pollution research international May 18, 2020
Considering the time-varying, uncertain and non-linear properties of the wastewater treatment process (WWTPs), a novel multi-kernel relevance vector machine (MRVM) soft sensor based on time difference (TD) is proposed to predict the quality-relevant ...
Algorithms Artificial Intelligence Support Vector Machine Wastewater
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Modeling water flux in osmotic membrane bioreactor by adaptive network-based fuzzy inference system and artificial neural network.

Bioresource technology Apr 18, 2020
Osmotic Membrane Bioreactor (OMBR) is an emerging technology for wastewater treatment with membrane fouling as a major challenge. This study aims to develop Adaptive Network-based Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) mod...
Osmosis Fuzzy Logic Neural Networks, Computer Bioreactors Wastewater Membranes, Artificial Water
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Monitoring and detecting faults in wastewater treatment plants using deep learning.

Environmental monitoring and assessment Jan 29, 2020
Wastewater treatment plants use many sensors to control energy consumption and discharge quality. These sensors produce a vast amount of data which can be efficiently monitored by automatic systems. Consequently, several different statistical and lea...
Environmental Monitoring Wastewater Deep Learning Neural Networks, Computer Machine Learning
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Rapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewater.

Journal of medical toxicology : official journal of the American College of Medical Toxicology Jan 9, 2020
INTRODUCTION: Accurate data regarding opioid use, overdose, and treatment is important in guiding community efforts at combating the opioid epidemic. Wastewater-based epidemiology (WBE) is a potential method to quantify community-level trends of opio...
Substance-Related Disorders Feasibility Studies Analgesics, Opioid Mass Spectrometry Water Pollutants, Chemical Robotics Naloxone Narcotic Antagonists Opioid Epidemic Opioid-Related Disorders Solid Phase Extraction North Carolina Female Adult Male Middle Aged Environmental Monitoring Urban Health Humans Wastewater
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In vitro selection of DNA aptamers and their integration in a competitive voltammetric biosensor for azlocillin determination in waste water.

Analytica chimica acta Dec 16, 2019
The uncontrolled usage of veterinary antibiotics has led to their widespread pollution in waterways and milk products. Potential impact of antibiotic residues on the environment and human health such as increased antibiotic resistance of microorganis...
DNA Electrochemical Techniques Limit of Detection Wastewater Azlocillin Aptamers, Nucleotide Anti-Bacterial Agents Base Sequence Biosensing Techniques Drinking Water Water Pollutants, Chemical
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BP-ANN Model Coupled with Particle Swarm Optimization for the Efficient Prediction of 2-Chlorophenol Removal in an Electro-Oxidation System.

International journal of environmental research and public health Jul 10, 2019
Electro-oxidation is an effective approach for the removal of 2-chlorophenol from wastewater. The modeling of the electrochemical process plays an important role in improving the efficiency of electrochemical treatment and increasing our understandin...
Electrochemical Techniques Water Purification Kinetics Neural Networks, Computer Water Pollutants, Chemical Wastewater Biological Oxygen Demand Analysis Chlorophenols Oxidation-Reduction
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An influent responsive control strategy with machine learning: Q-learning based optimization method for a biological phosphorus removal system.

Chemosphere Jun 14, 2019
Biological phosphorus removal (BPR) is an economical and sustainable processes for the removal of phosphorus (P) from wastewater, achieved by recirculating activated sludge through anaerobic and aerobic (An/Ae) processes. However, few studies have sy...
Waste Disposal, Fluid Sewage Models, Theoretical Metabolism Machine Learning Water Pollutants, Chemical Bioreactors Biological Oxygen Demand Analysis Wastewater Models, Biological Algorithms Phosphorus
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The application of machine learning methods for prediction of metal sorption onto biochars.

Journal of hazardous materials Jun 3, 2019
The adsorption of six heavy metals (lead, cadmium, nickel, arsenic, copper, and zinc) on 44 biochars were modeled using artificial neural network (ANN) and random forest (RF) based on 353 dataset of adsorption experiments from literatures. The regres...
Adsorption Regression Analysis Charcoal Hydrogen-Ion Concentration Cations Metals, Heavy Water Purification Biomass Water Pollutants, Chemical Machine Learning Wastewater Nerve Net
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