Assessment of Shelf Life of Processed Cheese by Expert Cascade Artificial Neural Network Computing Models



This paper highlights  the significance of cascade single layer models for predicting the shelf life of processed cheese stored at 7-8oC. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient were used for testing the prediction ability of the developed models. The developed cascade model with a combination of 5à8à1 showed excellent agreement between the actual and the predicted values, suggesting that single layer cascade models are efficient in predicting the shelf life of processed cheese.


artificial neural network; artificial intelligence; cascade; shelf life prediction; processed cheese

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Print ISSN: 2180-3536

Online ISSN: 2180-3706



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