AIMC Topic: Sewage

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Optimal Selection of Sewage Treatment Technologies in Town Areas: A Coupled Multi-Criteria Decision-Making Model.

Environmental management Jul 28, 2020
In recent years, the development of sewage treatment technologies has made many treatment options available in towns. Selecting the most appropriate alternative (MAA) can make the best use of existing resources to achieve the optimal effect, which ha...
Fuzzy Logic Sewage Rivers China Cities Animals
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Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

Microbiome Feb 11, 2020
BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene t...
Metagenomics Archaea Metagenome Bioreactors Sewage Bacteria RNA, Ribosomal, 16S Machine Learning
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Predicting the higher heating value of syngas pyrolyzed from sewage sludge using an artificial neural network.

Environmental science and pollution research international Dec 6, 2019
Sludge pyrolysis is a complex process including complicated reaction chemistry, phase transition, and transportation phenomena. To better evaluate the use of syngas, the monitoring and prediction of a higher heating value (HHV) is necessary. This stu...
Heating Waste Disposal, Fluid Pyrolysis Catalysis Sewage Neural Networks, Computer Temperature
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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...
Models, Theoretical Water Pollutants, Chemical Bioreactors Algorithms Waste Disposal, Fluid Sewage Metabolism Biological Oxygen Demand Analysis Models, Biological Phosphorus Machine Learning Wastewater
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Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process.

Microbiome Apr 17, 2019
BACKGROUND: Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activ...
Kinetics Sewage Microbial Consortia Bacteria RNA, Ribosomal, 16S Bioreactors Machine Learning Wastewater
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Comparative study of different wavelet-based neural network models to predict sewage sludge quantity in wastewater treatment plant.

Environmental monitoring and assessment Feb 16, 2019
In this study, artificial neural networks (ANNs) including feed forward back propagation neural network (FFBP-NN) and the radial basis function neural network (RBF-NN) were applied to predict daily sewage sludge quantity in wastewater treatment plant...
Artificial Intelligence Neural Networks, Computer Environmental Monitoring Wastewater Waste Disposal, Fluid Sewage
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Production of lipid-containing algal-bacterial polyculture in wastewater and biomethanation of lipid extracted residues: Enhancing methane yield through hydrothermal pretreatment and relieving solvent toxicity through co-digestion.

The Science of the total environment Nov 6, 2018
The feasibility of generating a lipid-containing algal-bacterial polyculture biomass in municipal primary wastewater and enhancing biomethanation of lipid-extracted algal residues (LEA) through hydrothermal pretreatment and co-digestion with sewage s...
Kinetics Bacteria Coculture Techniques Solvents Lipids Sewage Wastewater Chlorophyta Methane Biomass
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The key role of inoculated sludge in fast start-up of sequencing batch reactor for the domestication of aerobic granular sludge.

Journal of environmental sciences (China) Sep 7, 2018
Two types of inoculated sludges, granular sludge that had been stored at -20°C and activated sludge, were investigated for the domestication of aerobic granular sludges (AGSs) in sequencing batch reactors (SBRs). The results showed that using the sto...
Water Pollutants, Chemical Bioreactors Nitrogen Aerobiosis Phosphorus Ammonium Compounds Biomass Sewage Waste Disposal, Fluid Biological Oxygen Demand Analysis
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Evaluation and optimization of anammox baffled reactor (AnBR) by artificial neural network modeling and economic analysis.

Bioresource technology Sep 4, 2018
Anammox baffled reactor (AnBR) had a moderate start-up period of 53 days. Interestingly, tangled relationships between key parameters affecting anammox performance were observed, i.e., polynomial function for nitrogen loading rate (NLR) with extracel...
Neural Networks, Computer Nitrogen Biomass Sewage Bioreactors
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Modeling of an activated sludge process for effluent prediction-a comparative study using ANFIS and GLM regression.

Environmental monitoring and assessment Aug 1, 2018
In this paper, nonlinear system identification of the activated sludge process in an industrial wastewater treatment plant was completed using adaptive neuro-fuzzy inference system (ANFIS) and generalized linear model (GLM) regression. Predictive mod...
Models, Chemical Sewage Organic Chemicals Water Pollution, Chemical Environmental Monitoring Neural Networks, Computer Linear Models Fuzzy Logic Wastewater
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