Analyzing shelf life of processed cheese by soft computing

Feedforward soft computing multilayer models were developed for analyzing shelf life of processed cheese. The models were trained with 80% of total observations and validated with 20% of the remaining data. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were used in order to compare the prediction ability of the developed models. From the study, it is concluded that feedforward multilayer models are good in predicting the shelf life of processed cheese stored at 7-8o C.

Keywords:

Feedforward Backpropagation , Soft Computing , Artificial Intelligence , Shelf Life , Processed Cheese , ANN