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

TitleEvaluation of Shelf Life of Processed Cheese by Implementing Neural Computing Models
Publication TypeJournal Article
Year of Publication2012
AuthorsGoyal, S., and G. K. Goyal
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueSpecial Issue on Distributed Computing and Artificial Intelligence
Volume1
Number5
Date Published06/2012
Pagination61-64
Abstract

For predicting the shelf life of processed cheese stored at 7-8 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.

KeywordsArtificial Intelligence, Artificial Neural Networks, Elman, Processed Cheese, Shelf Life
DOI10.9781/ijimai.2012.158
URLhttp://www.ijimai.org/journal/sites/default/files/IJIMAI20121_5_8.pdf
AttachmentSize
IJIMAI20121_5_8.pdf342 KB