Abstract
Hybrid process models, which simultaneously utilize artificial neural networks, fuzzy rule systems, and mathematical balance equations, are shown to improve industrial-scale biotechnical production processes. As an example the application of hybrid models to the repeated fed-batch production of a recombinant therapeutical protein from mammalian cells will be discussed. State estimation, prediction and on-line determination of optimal feeds will be considered.
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