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Anaerobiosis

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Interpretable machine learning for predicting biomethane production in industrial-scale anaerobic co-digestion.

The Science of the total environment
The objective of this study is to apply machine learning models to accurately predict daily biomethane production in an industrial-scale co-digestion facility. The methodology involved applying elasticnet, random forest, and extreme gradient boosting...

Data-driven fault detection methods for detecting small-magnitude faults in anaerobic digestion process.

Water science and technology : a journal of the International Association on Water Pollution Research
Early detection of small-magnitude faults in anaerobic digestion (AD) processes is a mandatory step for preventing serious consequence in the future. Since volatile fatty acids (VFA) accumulation is widely suggested as a process health indicator, a V...

Prediction of anaerobic digestion performance and identification of critical operational parameters using machine learning algorithms.

Bioresource technology
Machine learning has emerges as a novel method for model development and has potential to be used to predict and control the performance of anaerobic digesters. In this study, several machine learning algorithms were applied in regression and classif...

Innovation hotspots in food waste treatment, biogas, and anaerobic digestion technology: A natural language processing approach.

The Science of the total environment
The objective of this study is to apply natural language processing to identifying innovative technology trends related to food waste treatment, biogas, and anaerobic digestion. The methodology used involved analyzing large volumes of text data mined...

Use of artificial neuronal networks for prediction of the control parameters in the process of anaerobic digestion with thermal pretreatment.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This article focuses on the analysis of the behavior patterns of the variables involved in the anaerobic digestion process. The objective is to predict the impact factor and the behavior pattern of the variables, i.e., temperature, pH, volatile solid...

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

Environmental science and pollution research international
Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. Th...

Feedforward neural network model estimating pollutant removal process within mesophilic upflow anaerobic sludge blanket bioreactor treating industrial starch processing wastewater.

Bioresource technology
In this a, three-layered feedforward-backpropagation artificial neural network (BPANN) model was developed and employed to evaluate COD removal an upflow anaerobic sludge blanket (UASB) reactor treating industrial starch processing wastewater. At the...

[Effect of the Food to Mass Ratio and Hydraulic Retention Time on Hydrogen Production from Fruit and Vegetable Waste].

Huan jing ke xue= Huanjing kexue
Semi-continuous biogas production from fruit and vegetable waste by medium temperature anaerobic fermentation was conducted. Hydrogen production under different food-microorganism ratios (F/M 0.5, 0.75, 1.0, 1.5) and hydraulic retention times (HRT) (...

Artificial intelligence based model for optimization of COD removal efficiency of an up-flow anaerobic sludge blanket reactor in the saline wastewater treatment.

Water science and technology : a journal of the International Association on Water Pollution Research
The complex non-linear behavior presented in the biological treatment of wastewater requires an accurate model to predict the system performance. This study evaluates the effectiveness of an artificial intelligence (AI) model, based on the combinatio...

Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.

Bioresource technology
Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato s...