Time – Delay Simulated Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese

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Author(s)

Sumit Goyal 1,* Gyanendra Kumar Goyal 2

1. Sr. Research Fellow, National Dairy Research Institute, Karnal, India

2. Emeritus Scientist, National Dairy Research Institute, Karnal, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2012.05.05

Received: 20 Aug. 2011 / Revised: 10 Nov. 2011 / Accepted: 16 Jan. 2012 / Published: 8 May 2012

Index Terms

ANN, Artificial Intelligence, Time-Delay, Processed Cheese, Shelf Life, Prediction

Abstract

This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8oC. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and nash - Sutcliffe coefficient were used for calculating the prediction capability of the developed models. Time-Delay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 7-8^oC.

Cite This Paper

Sumit Goyal, Gyanendra Kumar Goyal, "Time – Delay Simulated Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.5, pp.30-37, 2012. DOI:10.5815/ijisa.2012.05.05

Reference

[1]Kalogirou, S. A. Applications of artificial neural-networks for energy systems [J], Applied Energy, 2000,67:17-35

[2]Palau, A., Velo,E., and Puigjaner,L. Use of neural networks and expert systems to control a gas/solid sorption chilling machine [J]. International Journal of Refrigeration, 1999, 22: 59-66.

[3]D. D. Massie, Neural-network fundamentals for scientists and engineers, ECOS’01 4-6 July, Istanbul, Turkey, 2001

[4]Martins, R. C., Lopes, V.V., Vicente, A. A. and Teixeira, J. A. Computational shelf-life dating: complex systems approaches to food quality and safety [J]. Food and Bioprocess Technology, 2008, 1(3): 207-222.

[5]http://www.dtreg.com/mlfn.htm (accessed on 18.5.2011).

[6]Goyal, Sumit and Goyal, G. K. Central nervous system based computing models for shelf life prediction of soft mouth melting milk cakes [J]. International Journal of Information Technology and Computer Science, 2012 (accepted for publication).

[7]http://commons.wikimedia.org/wiki/Time_Delay_Neural_Network (accessed on 30.5.2011)

[8]http://en.wikipedia.org/wiki/Time_delay_neural_networkTraining ANN(accessed on 22.7.2011)

[9]Shankar, T.J. and Bandyopadhyay, S. Prediction of extrudate properties using artificial neural networks [J]. Food and Bioproducts Processing, 2007, 85(C1): 29-33.

[10]Rahman, M.S. Towards prediction of porosity in foods during drying: A brief review [J]. Drying Technology, 2001, 19(1): 3-15.

[11]Goyal, Sumit and Goyal, G. K. Study on single and double hidden layers of cascade artificial neural intelligence neurocomputing models for predicting sensory quality of roasted coffee flavoured sterilized drink [J]. International Journal of Applied Information Systems, 2012, 1(3): 1-4.

[12]Goyal, Sumit and Goya, G. K. Brain based artificial neural network scientific computing models for shelf life prediction of cakes [J]. Canadian Journal on Artificial Intelligence, Machine Learning and Pattern Recognition, 2011, 2(6): 73-77.

[13]Goyal, Sumit and Goyal, G. K. Simulated neural network intelligent computing models for predicting shelf life of soft cakes [J]. Global Journal of Computer Science and Technology, 2011, 11(14): Version 1.0, 29-33.

[14]Goyal, Sumit and Goyal, G. K. Advanced computing research on cascade single and double hidden layers for detecting shelf life of kalakand: An artificial neural network approach [J]. International Journal of Computer Science & Emerging Technologies, 2011, 2(5): 292-295.

[15]Goyal, Sumit and Goyal, G. K. Application of artificial neural engineering and regression models for forecasting shelf life of instant coffee drink [J]. International Journal of Computer Science Issues, 2011, 8(4): 1, 320-324

[16]Goyal, Sumit and Goyal, G. K. Cascade and feedforward backpropagation artificial neural networks models for prediction of sensory quality of instant coffee flavoured sterilized drink [J]. Canadian Journal on Artificial Intelligence, Machine Learning and Pattern Recognition, 2011, 2(6):78-82.

[17]Goyal, Sumit and Goyal, G. K. Development of neuron based artificial intelligent scientific computer engineering models for estimating shelf life of instant coffee sterilized drink [J]. International Journal of Computational Intelligence and Information Security, 2011, 2(7): 4 – 12

[18]Goyal, Sumit and Goyal, G. K. A new scientific approach of intelligent artificial neural network engineering for predicting shelf life of milky white dessert jeweled with pistachio [J]. International Journal of Scientific and Engineering Research, 2011, 2(9): 1-4.

[19]Goyal, Sumit and Goyal, G. K. Radial basis artificial neural network computer engineering approach for predicting shelf life of brown milk cakes decorated with almonds [J]. International Journal of Latest Trends in Computing 2011, 2(3): 434-438.

[20]Goyal, Sumit and Goyal, G.K. Development of intelligent computing expert system models for shelf life prediction of soft mouth melting milk cakes [J].International Journal of Computer Applications 2011, 25(9): 41-44.

[21]http://www.softcomputing.net/ann_chapter.pdf (accessed on 15.7.2011)

[22]http://www.heatonresearch.com/articles/5/page2.html. (accessed on 22.5.2011)