TY - JOUR
T1 - Thermal conductivity prediction of fruits and vegetables using neural networks
AU - Hussain, Mohamed Azlan
AU - Rahman, M. Shafiur
PY - 1999
Y1 - 1999
N2 - Artificial neural network was used to predict the thermal conductivity of various fruits and vegetables (apples, pears, corn starch, raisins and potatoes). Neural networks was also used to model the error between the experimental value and that of the theoretical model developed. Two separate networks were used to perform these separate tasks. The optimum configuration of the networks was obtained by trial and error basis using the multilayered approach with the backpropagation and Levenberg-Marquardt Methods used concurrently in the training of the networks. The results showed that the these networks has the ability to model the thermal conductivity as well as to predict the model/experimental error accurately. The networks can then be used as correction factor to the model in a hybrid approach and gave better prediction of thermal conductivity than the model itself.
AB - Artificial neural network was used to predict the thermal conductivity of various fruits and vegetables (apples, pears, corn starch, raisins and potatoes). Neural networks was also used to model the error between the experimental value and that of the theoretical model developed. Two separate networks were used to perform these separate tasks. The optimum configuration of the networks was obtained by trial and error basis using the multilayered approach with the backpropagation and Levenberg-Marquardt Methods used concurrently in the training of the networks. The results showed that the these networks has the ability to model the thermal conductivity as well as to predict the model/experimental error accurately. The networks can then be used as correction factor to the model in a hybrid approach and gave better prediction of thermal conductivity than the model itself.
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U2 - 10.1080/10942919909524596
DO - 10.1080/10942919909524596
M3 - Article
AN - SCOPUS:0032591132
SN - 1094-2912
VL - 2
SP - 121
EP - 137
JO - International Journal of Food Properties
JF - International Journal of Food Properties
IS - 2
ER -