Modeling and simulation of co-digestion performance with artificial neural network for prediction of methane production from tea factory waste with co-substrate of spent tea waste

[Display omitted] •ANN model was used to simulate for prediction and maximization of ACd.•Bayesian Regularization algorithm showed the best performance.•According to the ANN model, the co-digestion might improve the methane yield up to 183% compared to mono substrates. The production of biofuel from...

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Bibliographic Details
Published in:	Fuel (Guildford) Vol. 306; p. 121715
Main Authors:	Özarslan, Saliha, Abut, Serdar, Atelge, M.R., Kaya, M., Unalan, S.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 15.12.2021 Elsevier BV
Subjects:	Algorithms ANN modeling ANN simulation Artificial neural networks Availability Batch reactors Bayesian analysis Bayesian regularization algorithm Best management practices Biodegradability Biodegradation Biodiesel fuels Biofuels Biogas Computer simulation Digestion Environmental hazards Environmental management Industrial wastes Methane Neural networks Regularization Spent tea waste Substrates Synergistic effect Tea Tea factory waste Waste management Tea factory waste ANN simulation ANN modeling Biogas Spent tea waste Bayesian regularization algorithm
ISSN:	0016-2361, 1873-7153
Online Access:	Get full text
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