Model construction and optimization for raising the concentration of industrial bioethanol production by using a data-driven ANN model
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DOI: 10.1016/j.renene.2023.119031
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- Sahar Safarian & Seyed Mohammad Ebrahimi Saryazdi & Runar Unnthorsson & Christiaan Richter, 2021. "Artificial Neural Network Modeling of Bioethanol Production Via Syngas Fermentation," Biophysical Economics and Resource Quality, Springer, vol. 6(1), pages 1-13, March.
- Li, Xinzhe & Dong, Yufeng & Chang, Lu & Chen, Lifan & Wang, Guan & Zhuang, Yingping & Yan, Xuefeng, 2023. "Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model," Renewable Energy, Elsevier, vol. 205(C), pages 574-582.
- Małgorzata Smuga-Kogut & Tomasz Kogut & Roksana Markiewicz & Adam Słowik, 2021. "Use of Machine Learning Methods for Predicting Amount of Bioethanol Obtained from Lignocellulosic Biomass with the Use of Ionic Liquids for Pretreatment," Energies, MDPI, vol. 14(1), pages 1-16, January.
- Grahovac, Jovana & Jokić, Aleksandar & Dodić, Jelena & Vučurović, Damjan & Dodić, Siniša, 2016. "Modelling and prediction of bioethanol production from intermediates and byproduct of sugar beet processing using neural networks," Renewable Energy, Elsevier, vol. 85(C), pages 953-958.
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Keywords
Artificial neural network model; Bioethanol concentration; Model development; Optimization; Synthesized data technique;All these keywords.
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