Evaluation of drying and degradation kinetics using neurocomputing

Application of artificial neural network (ANN) in chemical engineering with special reference to drying process is discussed in the paper. Two types of networks: RBF and MLP, which are important for the description of a process dynamics, are presented. As an example drying and degradation of ascorbic acid in agricultural products are considered. The final conclusion supported with experimental data states that the type of ANN should be carefully selected because the real capability of the ANN model for a given dynamic problem is expressed in recurrent working mode.

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