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Sumit Goyal
National Dairy Research Institute, Karnal
India
Gyanendra Kumar Goyal
National Dairy Research Institute, Karnal
India
Vol. 2 No. 3 (2013), Articles, pages 09-13
DOI: https://doi.org/10.14201/ADCAIJ201426913
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Abstract

This paper highlights the significance of feedforward artificial neural network models for predicting shelf life of roasted coffee falvoured sterilized drink. Coffee is one of the most important products for trade in international market. Single as well as multilayer models were explored and different backpropagation algorithms were investigated, Root mean square error and coefficient of determination R2 were used to compare the prediction performance of single and multilayer feedforward ANN models. Experimental results suggested that multilayer models take less time and give better results as compared to single layer ANN models for prediction of sensory quality of roasted coffee falvoured sterilized drink..

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References

CHAYJAN, R.A. & ASHARI, M. E. (2010). Modeling isosteric heat of soya bean for desorption energy estimation using neural network approach. Chilean Journal of Agricultural Research, 70(4), 616-625.

DEMUTH, H., BEALE, M. & HAGAN, M. Neural Network Toolbox User’s Guide. The MathWorks, Inc., Natrick, USA.

GOYAL, G.K. & GOYAL, SUMIT Cascade artificial neural network models for predicting shelf life of processed cheese. Journal of Advances in Information Technology, 4(2), 80-83.

GOYAL, SUMIT & GOYAL, G.K. Simulated neural network intelligent computing models for predicting shelf life of soft cakes. Global Journal of Computer Science and Technology, 11(14), 29-33.

GOYAL, SUMIT & GOYAL, G.K. (2011B). Application of artificial neural engineering and regression models for forecasting shelf life of instant coffee drink. International Journal of Computer Science Issues, 8(4), 320-324

GOYAL, SUMIT & GOYAL, G.K. (2011C). Development of intelligent computing expert system models for shelf life prediction of soft mouth melting milk cakes. International Journal of Computer Applications, 25(9), 41-44.

GOYAL, SUMIT & GOYAL, G.K. Application of artificial neural engineering and regression models for forecasting shelf life of instant coffee drink. International Journal of Computer Science Issues, 8(4), 320-324.

GOYAL, SUMIT & GOYAL, G.K. Intelligent artificial neural network computing models for predicting shelf life of processed cheese. Intelligent Decision Technologies, 7(2), 107-111.

GOYAL, SUMIT & GOYAL, G.K. Artificial vision for estimating shelf life of burfi. Journal of Nutritional Ecology and Food Research, 1(2), 134-13

GOYAL, SUMIT (2013). Artificial neural networks (ANNs) in food science – A review. International Journal of Scientific World, 1(2), 19-28.

http://dictionary.reverso.net/english-cobuild/shelf%20life (accessed on 2.1.2011).

http://hassam.hubpages.com/hub/Artificial-Intelligence-And-Artificial-Neural-Networks (accessed on 5.1.2011).

http://www.heatonresearch.com/node/703 (accessed on 4.1.2011).

SIRIPATRAWAN, U. & JANTAWAT, P. Artificial neural network approach to simultaneously predict shelf life of two varieties of packaged rice snacks. International Journal of Food Science & Technology, 44(1), 42–49