Modelling fed-batch fermentation processes: An approach based on artificial neural networks

Publicado em "2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008)", ISBN 978-3-540-85860-7Artificial Neural Networks (ANNs) have shown to be powerful tools for solving several problems which, due to their complexity, are extremely difficult to unravel with other methods. Their capabilities of massive parallel processing and learning from the environment make these structures ideal for prediction of nonlinear events. In this work, a set of computational tools are proposed, allowing researchers in Biotechnology to use ANNs for the modelling of fed-batch fermentation processes. The main task is to predict the values of kinetics parameters from the values of a set of state variables. The tools were validated with two case studies, showing the main functionalities of the application.This work was supported by the Portuguese FCT under project POSC/EIA/59899/2004