Application of artificial neural networks to investigate the drying of cooked rice.

Commercially available neural networks software was applied for prediction
of processing parameters with reference to the product quality of the dehydrated
cooked rice. These results were verified with experimental data. The experimental
results indicate good concurrence with the predicted data. A small capacity
vibrofluidized bed drier was used to conduct the experimental studies. The inlet
air temperature of 160C to 180C, the inlet air velocity of 3 to 6 ms -' and the
resident time of 5 to 8 min were used in the study. The optimized process
parameters were identified. The operation of the neural network model is
discussed. The trained model can be applied in a nonlinear model predictive
scheme to control the product moisture content.