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  • Study on Single and Double Hidden Layers of Cascade Artificial Neural Intelligence Neurocomputing Models for Predicting Sensory Quality of Roasted Coffee Flavoured Sterilized Drink

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Number 3

Study on Single and Double Hidden Layers of Cascade Artificial Neural Intelligence Neurocomputing Models for Predicting Sensory Quality of Roasted Coffee Flavoured Sterilized Drink

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  • Sumit Goyal and Gyanendra Kumar Goyal 2012. Study on Single and Double Hidden Layers of Cascade Artificial Neural Intelligence Neurocomputing Models for Predicting Sensory Quality of Roasted Coffee Flavoured Sterilized Drink. International Journal of Applied Information Systems. 1, 3 (February 2012), 1-4. DOI=http://dx.doi.org/10.5120/ijais450122 
  • @article{10.5120/ijais2017451568,
author = {Sumit Goyal and Gyanendra Kumar Goyal },
title = {Study on Single and Double Hidden Layers of Cascade Artificial Neural Intelligence Neurocomputing Models for Predicting Sensory Quality of Roasted Coffee Flavoured Sterilized Drink},
journal = {International Journal of Applied Information Systems},
issue_date = {February 2012},
volume = {1},
number = {},
month = {February},
year = {2012},
issn = {},
pages = {1-4},
numpages = {},
url = {/archives/volume1/number3/70-0122},
doi = { 10.5120/ijais12-450122},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450122
%A Sumit Goyal
%A Gyanendra Kumar Goyal 
%T 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
%@ 
%V 1
%N 
%P 1-4
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

For centuries, coffee has been brewed and consumed in households, hot shops and restaurants. Today flavoured milks have become very popular and they contain nutrients as compared with soft drinks. Sterilized milk is the product made by heating milk to high temperature (121o C) with 15 m holding time so that it remains fit for human consumption for longer time at room temperature. Efficiency of single and double hidden layers of Cascade neurocomputing models for prediction of sensory quality of roasted coffee flavoured sterilized drink were studied. Colour and appearance, viscosity, flavour and sediment were taken as input parameters, while overall acceptability was used as output parameter. The results of cascade neurocomputing models were calculated with two types of prediction performance measures, viz., root mean square error and coefficient of determination R2.The study revealed that more the number of neurons in single hidden layer, less the error for cascade neurocomputing models ( RMSE:0.00011; R2 : 0.999999; neurons:50).

References

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  3. Goyal, Sumit and Goyal, G.K. 2011a. Application of artificial neural engineering and regression models for forecasting shelf life of instant coffee drink. International Journal of Computer Science Issues, 8(4), No 1, pp.320-324.
  4. Goyal, Sumit and Goyal, G.K. 2011b. Development of intelligent computing expert system models for shelf life prediction of soft mouth melting milk cakes. International Journal of Computer Applications,25(9), pp.41-44.
  5. Goyal. Sumit and Goyal, G.K. 2011c. Development of neuron based artificial intelligent scientific computer engineering models for estimating shelf life of instant coffee sterilized drink. International Journal of Computational Intelligence and Information Security, 2(7), pp.4-12.
  6. Goyal, Sumit and Goyal, G.K. 2011d. Simulated neural network intelligent computing models for predicting shelf life of soft cakes. Global Journal of Computer Science and Technology, 11(14), Version 1.0, pp. 29-33.
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Keywords

ANN, Cascade, Neurocomputing, Sensory Quality, Coffee, Prediction

Index Terms

Computer Science
Information Sciences