Abstract
A hybrid neural model was developed for the alcoholic fermentation by Zymomonas mobilis. This model is composed by the mass-balance equations of the process and neural networks, which describe the kinetic rates. Strategies that combines scarce experimental data with approximate models of the process were used to generate new data for the training of the networks, minimizing the number of experiments required. The proposed hybrid neural methodology uses all the information available about the process to deal with the difficulties in the development of the model.
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© 1999 Springer Science+Business Media New York
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da Henriques, A.W.S., da Costa, A.C., Alves, T.L.M., Lima, E.L. (1999). A Hybrid Neural Model of Ethanol Production by Zymomonas mobilis . In: Davison, B.H., Finkelstein, M. (eds) Twentieth Symposium on Biotechnology for Fuels and Chemicals. Applied Biochemistry and Biotechnology. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-4612-1604-9_26
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DOI: https://doi.org/10.1007/978-1-4612-1604-9_26
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-4612-7214-4
Online ISBN: 978-1-4612-1604-9
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