Radial Basis (Exact Fit) Artificial Neural Network Technique for Estimating Shelf Life of Burfi
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| Title | Radial Basis (Exact Fit) Artificial Neural Network Technique for Estimating Shelf Life of Burfi |
| Authors | |
| Abstract | Radial basis (exact fit) artificial neural network model for estimating the shelf life of burfi stored at 30º C has been developed. Input variables for developing the models were moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value; and the overall acceptability score was output variable. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient were applied in order to compare the prediction ability of the developed models. High correlation was found between training and validation data, indicating that the developed Radial basis (exact fit) ANN models are good for estimating the shelf life of burfi. |
| Publisher | World Science Publisher |
| Date | 2012-04-09 |
| Source | 2166-2924 |
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