The experimental performance and artificial neural network modeling of rice drying in BAU-STR dryer is presented in this paper. The dryer consists of a biomass stove as a heat source, a perforated inner bin and a perforated outer bin with annular space for grains, and a blower (1 hp) to supply heated air. The dryer capacity was 500 kg of freshly harvested rice. Twenty experimental runs were conducted to investigate the experimental performance of the dryer for drying of rice. An independent multilayer neural network approach was used to predict the performance of the BAU-STR dryer for drying of rice. Ten sets of experimental data were used for training using back propagation algorithm and another ten sets of data were used for testing the artificial neural network model. The prediction of the performance of the dryer was found to be excellent after it was adequately trained. The statistical analysis showed that the errors (MSE and RMSE) were within and acceptable range of ±5% with a coefficient of determination (R²) of 99%. The model can be used to predict the potential of the dryer for different locations, and can also be used in a predictive optimal control algorithm.

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independent multilayer neural network approach back propagation algorithm determination predictive optimal control algorithm baustr dryer model drying of rice

Md. Ashraful Alam,Md. Monjurul Alam,Chayan Kumer Saha,Jagger Harvey,Bilash Kanti Bala,Md. Ali Ashraf,.Neural network modeling of drying of rice in BAU-STR dryer. 54 (11),3297–3305.

Md. Ashraful Alam, et al."Neural network modeling of drying of rice in BAU-STR dryer" 54

Md. Ashraful Alam,Md. Monjurul Alam,Chayan Kumer Saha,Jagger Harvey,Bilash Kanti Bala,Md. Ali Ashraf,"Neural network modeling of drying of rice in BAU-STR dryer"