This paper discusses the opportunities for the use of artificial intelligence methods for the modelling of drying processes. The main emphasis is given to the artificial neural network (ANN) modelling of heat and mass transfer in the course of grain and hay drying. The main conclusion is that a properly selected structure of neural network model can be used to determine the moisture distribution in a fixed-bed dryer. It is important to mention that, in addition to other factors, the selection of training and validation input data for the ANN model has a strong influence on the applicability.
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István Farkas (2013) studied this question.
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