An artificial neural network for prediction of zeleny sedimentation volume of wheat flour
2008
Razmi-Rad, E. (Sarab Azad Univ. (Iran). Food Science and Engineering Group) | Ghanbarzadeh, B. (University of Tabriz (Iran). Dept. of Food Science and Technology) | Rashmekarim, J. (Research Center of Iran Seed and Plant Improvements Inst., Tabriz (Iran))
The sedimentation volume of gluten in flour dispersion indicates its gluten quality and thus the bread making quality of the flour. Artificial neural network (ANN) modeling was used to model the sedimentation property of wheat flour as a function of total protein, wet gluten and hardness index. In developing the ANN model, several configurations were evaluated. The optimal ANN configuration was found to be a network consisting of one hidden layer with nine neurons. The number of iterations, learning rate and momentum coefficient had important effects on the optimal configuration. The optimal model was capable of predicting the Zeleny sedimentation value with a mean absolute error (MAE) of 3.922 and root mean square error (RMSE) of 4.561.
Показать больше [+] Меньше [-]Ключевые слова АГРОВОК
Библиографическая информация
Эту запись предоставил National Agricultural Research Centre