AIMC Topic: Wastewater

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Deep-learning based monitoring of FOG layer dynamics in wastewater pumping stations.

Water research Jul 31, 2021
Accumulation of fat, oil and grease (FOG) in the sumps of wastewater pumping stations is a common failure cause for these facilities. Floating solids are often not transported by the pump suction inlets and the individual solids can accumulate to sti...
Wastewater Netherlands Hydrocarbons Water Deep Learning
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Real-time monitoring of forward osmosis membrane fouling in wastewater reuse process performed with a deep learning model.

Chemosphere Feb 22, 2021
Monitoring fouling behavior for better understanding and control has recently gained increasing attention. However, there is no practical method for observing membrane fouling in real time, especially in the forward osmosis (FO) process. In this arti...
Water Purification Deep Learning Wastewater Osmosis Membranes, Artificial
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An osmotic membrane bioreactor-clarifier system with a deep learning model for simultaneous reduction of salt accumulation and membrane fouling.

Chemosphere Feb 6, 2021
This study investigates a novel hybrid configuration of an osmotic membrane bioreactor-clarifier (OMBRC) to achieve the simultaneous reduction of salt accumulation and membrane fouling. Compared with the conventional OMBR, the OMBRC demonstrated 14 t...
Osmosis Membranes, Artificial Artificial Intelligence Bioreactors Wastewater Deep Learning Water Purification
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Integrated Model for Understanding NO Emissions from Wastewater Treatment Plants: A Deep Learning Approach.

Environmental science & technology Jan 12, 2021
This study aims to demonstrate the application of deep learning to quantitatively describe long-term full-scale data observed from wastewater treatment plants (WWTPs) from the perspectives of process modeling, process analysis, and forecasting modeli...
Deep Learning Bioreactors Water Purification Nitrous Oxide Wastewater
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ANN based modelling of hydrodynamic cavitation processes: Biomass pre-treatment and wastewater treatment.

Ultrasonics sonochemistry Dec 28, 2020
We have developed artificial neural network (ANN) based models for simulating two application examples of hydrodynamic cavitation (HC) namely, biomass pre-treatment to enhance biogas and degradation of organic pollutants in water. The first case repo...
Biomass Neural Networks, Computer Wastewater Hydrodynamics Waste Disposal, Fluid
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Multivariate data-based optimization of membrane adsorption process for wastewater treatment: Multi-layer perceptron adaptive neural network versus adaptive neural fuzzy inference system.

Chemosphere Dec 11, 2020
Application of machine-learning methods to assess the batch adsorption of malachite green (MG) dye on chitosan/polyvinyl alcohol/zeolite imidazolate frameworks membrane adsorbents (CPZ) was investigated in this study. Our previous research results pr...
Adsorption Reproducibility of Results Fuzzy Logic Machine Learning Wastewater Neural Networks, Computer
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Multi-period evaluation and selection of rural wastewater treatment technologies: a case study.

Environmental science and pollution research international Aug 17, 2020
Rapid population growth and agricultural development are generating a considerable amount of effluents, which poses threats to the quality of rural water resources as well as sanitary conditions. However, with a range of rural wastewater treatment (W...
Water Resources Agriculture Technology Fuzzy Logic 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 (...
Bacteria Soil Water Quality Environmental Monitoring Neural Networks, Computer Wastewater Water Microbiology Morocco
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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. ...
Fatty Acids, Volatile Fermentation Anaerobiosis Wastewater 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 ...
Support Vector Machine Wastewater Artificial Intelligence Algorithms
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