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Evaluation of Shelf Life of Processed Cheese by Implementing Neural Computing Models

Authors :
Sumit Goyal
Gyanendra Kumar Goyal
Source :
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 1, Iss 5, Pp 61-64 (2012)
Publication Year :
2012
Publisher :
Universidad Internacional de La Rioja (UNIR), 2012.

Abstract

For predicting the shelf life of processed cheese stored at 7-8º C, Elman single and multilayer models were developed and compared. The input variables used for developing the models were soluble nitrogen, pH; standard plate count, Yeast & mould count, and spore count, while output variable was sensory score. 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. The Elman models got simulated very well and showed excellent agreement between the experimental data and the predicted values, suggesting that the Elman models can be used for predicting the shelf life of processed cheese.

Details

Language :
English
ISSN :
19891660
Volume :
1
Issue :
5
Database :
Directory of Open Access Journals
Journal :
International Journal of Interactive Multimedia and Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.21472d9f8e74fab98eaa583dc2ff542
Document Type :
article