An Artificial Neural Network (ANN) is a regressive machine learning algorithm composed of layered interconnected nodes. Essentially, this technique allows the estimation of process variables without the requirement of a process model. ANN are used to provide approximations to non-linear systems. Briefly, the network must receive an input from a set of data e.g. pH, NO3 concentration; which is then propagated by a hidden or intermediate layer to an outer layer, which finally predicts the variable of interest, e.g. biomass concentration. ANN are considered highly flexible models since they provide the possibility to handle large amounts of parameters and demonstrably approximate any function.
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Institute of Technical Chemistry
Leibniz University of Hannover
Callinstraße 5
30167 Hannover, Germany
Tel.: + 49 511 762 2253
Fax: + 49 511 762 3004
Email: lindner@iftc.-uni-hannover.de
