Time – Delay Simulated Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese

This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8o^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. Time-Delay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 7-8o^C.