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Neural Network Modelling of Fermentation Taking into Account Culture Memory

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Artificial Neural Nets and Genetic Algorithms

Abstract

In the present paper the problem of chemostat modelling using the neural networks is considered. Two kinds of neural network models taking into account the culture memory are proposed. The first one is a feedforward neural network with time delayed feedback connections from and to the output neurons. The second one is a feedforward neural network with time delayed feedback connections from the input neurons describing only the specific growth rate. The obtained neural network model is adopted in the classical nonlinear model. Simulation investigations and comparison of the both models are carried out. The interpretation of the parameters according to their biological means is made.

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Authors and Affiliations

  1. Institute of Control and System Research, Bulgarian Academy of Sciences, Acad.G.Bontchev Str., Bl.2, P.O. Box 79, 1113, Sofia, Bulgaria

    P. Koprinkova, M. Petrova & T. Patarinska

Authors
  1. P. Koprinkova
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  2. M. Petrova
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  3. T. Patarinska
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© 1995 Springer-Verlag/Wien

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Koprinkova, P., Petrova, M., Patarinska, T. (1995). Neural Network Modelling of Fermentation Taking into Account Culture Memory. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_21

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  • DOI: https://doi.org/10.1007/978-3-7091-7535-4_21

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82692-8

  • Online ISBN: 978-3-7091-7535-4

  • eBook Packages: Springer Book Archive

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