Title: Artificial Intelligence Elman Backpropagation Computing Models for Predicting Shelf Life of Processed Cheese

Author: Sumit Goyal and Gyanendra Kumar Goyal

Affiliation: National Dairy Research Institute, Karnal, India

Abstract: This paper presents the latency of Artificial Neural Network based Elman models for predicting the shelf life of processed stored at 30C. Soluble nitrogen, pH, standard plate count, yeast & mould count, and spore count were taken as input parameters, and sensory score as output parameter. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient performance measures were used for testing prediction potential of the developed models. In this study, Elman models predicted the shelf life of processed cheese very close to the experimentally determined shelf life.

Keywords: ANN, Shelf Life, Elman, Backpropagation, Processed Cheese.

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