Abstract
The objective of this chapter is to show that neural networks and fuzzy models can be incorporated in a semi-mechanistic modeling environment in a straightforward manner. The procedure is described by the development of a semi-mechanistic model for a real biochemical process, the enzymatic conversion of Penicillin-G. Two different type of black-box model parts:(i) a fuzzy model, and (ii) a neural network, are compared. Finally, the semi-mechanistic model is used to create enough data to make a neural network model for the full process, which fits better in real-time control strategies. Although the results do not carry over directly to other engineering fields, the main ideas, conclusions, and drawbacks will certainly hold for other application areas as well.
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