Abstract
This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8 o C. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and nash Sutcliffe coefficient were used for calculating the prediction capability of the developed models. TimeDelay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 78 o C.
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