ALGORITHM COMPUTING APPROACH OF GENERALIZED REGRESSION NEURAL NETWORK FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE

Abstract

The aim of this research is to develop Generalized Regression Artificial Neural Network (ANN) models for predicting shelf life of processed cheese. Processed cheese is protein rich food, and is a comparable supplement to meat protein. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffe Coefficient were used in order to compare the prediction ability of the developed models. The modeling results showed that there was exceptional agreement between the experimental data and the predicted values. The model might be an alternative method to control the expiration date of processed cheese.

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