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Reseach Article

Application of Artificial Neural Network for Standardization of Digital Colorimeter

Published on March 2012 by R. D. Khonde, S. L. Pandharipande
International Conference in Computational Intelligence
Foundation of Computer Science USA
ICCIA - Number 5
March 2012
Authors: R. D. Khonde, S. L. Pandharipande
3ab55cac-cd37-4875-8235-f767b4bdfb49

R. D. Khonde, S. L. Pandharipande . Application of Artificial Neural Network for Standardization of Digital Colorimeter. International Conference in Computational Intelligence. ICCIA, 5 (March 2012), 31-35.

@article{
author = { R. D. Khonde, S. L. Pandharipande },
title = { Application of Artificial Neural Network for Standardization of Digital Colorimeter },
journal = { International Conference in Computational Intelligence },
issue_date = { March 2012 },
volume = { ICCIA },
number = { 5 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 31-35 },
numpages = 5,
url = { /proceedings/iccia/number5/5126-1038/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference in Computational Intelligence
%A R. D. Khonde
%A S. L. Pandharipande
%T Application of Artificial Neural Network for Standardization of Digital Colorimeter
%J International Conference in Computational Intelligence
%@ 0975-8887
%V ICCIA
%N 5
%P 31-35
%D 2012
%I International Journal of Computer Applications
Abstract

Digital Colorimeter is used to estimate concentration of dye solutions of the given samples. This method of analysis is time consuming process and hence further repetitive analysis of samples can be eliminated by developing a model using artificial neural network (ANN), which correlates the concentration of dyes in the aqueous solutions with its Colorimeter readings. The present paper deals with a novel technique of standardization of a digital instrument using ANN for various synthetically prepared aqueous dyes solutions. The artificial neural network architecture is initialized through its training and the parameters of the neural network are adjusted to minimize the difference between the simulated and the measured values. Simulation and experimental studies illustrate the potential of the proposed method of using artificial neural network for standardization of digital Colorimeter.

References
  1. Anderson J.A., An Introduction to Neural Networks, Prentice-Hall of India, Pvt. Ltd., New Delhi,1999
  2. Daniel Svozil, Vladimir Kvasnicka, Jiri Pospichal, Introduction to multi-layer feed-forward neural networks, Chemometrics and Intelligent Laboratory Systems, vol.39, 1997, 43-62
  3. Rumelhart D. E. & McClleland, Back Propagation Training Algorithm Processing, M. I. T. Press, Cambridge Massachusetts, 1986
  4. Fan J. Y., Nikolau M. & White R. E., AIChE, vol.39(1) 1993, 82
  5. Hoskins J. C., Kaliyur K. M. & Himmelblau D. M., AIChE, vol.37(1), 1991, 137
  6. Watanabe K., Abe M., Kubota M. & Himmelblau D. M., AIChE, vol.35 (11), 1989, 1803
  7. Balsitor B. & Banergy S., AIChE, vol.44 (12), 1998, 2675
  8. Pandharipande S. L. & Badhe Y. P., Chem. Eng. World, vol.38(6), 2003, 70
  9. Zamankhan P., Malinen P. & Lepomaki H., AIChE, vol.43(7), 1997, 1684
  10. Baratti R., Vacca G. & Servida A., Hydrocarbon Processing, 1995, 35
  11. Pandharipande S. L., Agarwal R. S., Gogte B. B. & Badhe Y. P., Chem. Eng. World,vol. 38 (5), 2003, 78
  12. Pandharipande S. L. & Badhe Y. P., Chem. Eng. World, vol. 38(8), 2003, 82
  13. Pandharipande S. L. & Badhe Y. P., IIChe, vol.45(4), 2003, 256
  14. Pandharipande S. L. & Mandavgane S. A., Indian J. Chem. Technol., vol.11(6), 2004, 820
  15. Pandharipande S. L., Bhaise A. & Poharkar A., Chem. Eng. world, vol.39(1), 2004, 50
  16. Pandharipande S. L. & Badhe Y. P., J. Inst. Eng., vol.84(3), 2004, 65
  17. Pandharipande S. L. & Badhe Y. P., elite-ANN software, copyright ROC-SW-1471-2004
  18. Aboozar Khajeh, Hamid Modarress, and Mohsen MohsenMohsen-Nia, Solubility Prediction for Carbon Dioxide in Polymersby Artificial Neural Network, Iranian Polymer Journal,vol.16 (11), 2007, 759-768
Index Terms

Computer Science
Information Sciences

Keywords

Digital Colorimeter artificial neural network standardization simulation dyes