Abstract
This paper deals with the design of a neural network-based biomass concentration estimation system. This system is enhanced by the incorporation of information about the actual metabolism of the microorganism cultivated, which is taken from an on-line knowledge-based system. Two different design approaches have been investigated using the fed-batch cultivation of baker’s yeast as the model process. In the first, metabolic state (MS) data were passed as additional input to the neural network; in the second, these data were used to select a neural network suitable for the specific MS. Two neural network types—feed-forward (Levenberg-Marquardt) and cascade correlation—were applied to this system and tested, and the performances of these neural networks were compared.
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Vaněk, M., Hrnčiřík, P., Vovsík, J. et al. On-line estimation of biomass concentration using a neural network and information about metabolic state. Bioprocess Biosyst Eng 27, 9–15 (2004). https://doi.org/10.1007/s00449-004-0371-3
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DOI: https://doi.org/10.1007/s00449-004-0371-3