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Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control and a review of ANNs used in food processing. Also, examples of ANNs in food processing applications such as pasteurization control are illustrated.

This book addresses the issue of Model Predictive Control (MPC), supported by a real life application of temperature control in plate heat exchangers, as it is noticed that classical control strategies, for instance PI and PID, often give a relatively large variance in temperature. This results in the producer having to set up a higher control temperature set point than the actual needed one, which introduces energy loss as well as affecting sometimes the treated product itself. One way of reducing temperature variance in order to be able to lower the temperature set-point without...