%0 Journal Article %T Predicting Shelf Life of Burfi through Soft Computing %A Sumit Goyal %A Gyanendra Kumar Goyal %J International Journal of Information Engineering and Electronic Business %D 2012 %I MECS Publisher %X Soft computing cascade multilayer models were developed for predicting the shelf life of burfi stored at 30oC. The experimental data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were input variables, and the overall acceptability score was the output variable. The modelling results showed excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 = 0.993499439) and low RMSE (0.006500561), indicating that the developed model was able to analyze nonlinear multivariate data with very good performance, and can be used for predicting the shelf life of burfi. %K Soft computing %K artificial neural networks %K artificial intelligence %K burfi %K shelf life prediction %K cascade %U http://www.mecs-press.org/ijieeb/ijieeb-v4-n3/v4n3-4.html