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The New Similarity Measure for Fuzzy Sets and its Application to Medical Diagnostic Reasoning

by Pranamika Kakati
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 80 - Number 15
Year of Publication: 2013
Authors: Pranamika Kakati
10.5120/13936-1895

Pranamika Kakati . The New Similarity Measure for Fuzzy Sets and its Application to Medical Diagnostic Reasoning. International Journal of Computer Applications. 80, 15 ( October 2013), 13-17. DOI=10.5120/13936-1895

@article{ 10.5120/13936-1895,
author = { Pranamika Kakati },
title = { The New Similarity Measure for Fuzzy Sets and its Application to Medical Diagnostic Reasoning },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 80 },
number = { 15 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume80/number15/13936-1895/ },
doi = { 10.5120/13936-1895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:54:36.743051+05:30
%A Pranamika Kakati
%T The New Similarity Measure for Fuzzy Sets and its Application to Medical Diagnostic Reasoning
%J International Journal of Computer Applications
%@ 0975-8887
%V 80
%N 15
%P 13-17
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this article we shall deal with the new Similarity measure for Fuzzy sets based on the extended definition of complementation. Measuring similarity between Fuzzy sets is very important in the application of Fuzzy set theory. The new Similarity measure is based on the fact that Fuzzy membership function and Fuzzy membership value for the complement of a Fuzzy set are two different things. In this paper, our purpose is to put forward an algorithm to show the effectiveness of this new Similarity measure in supporting Medical Diagnostic reasoning. Also, we shall demonstrate the application of the proposed algorithm evaluating some collected data and verify the obtained results with the help of traditional Hamming Distance and Euclidean Distance measures.

References
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  8. Hongmei Ju (2008). "Entropy for Interval-valued Fuzzy Sets",Fuzzy information and engineering, Volume 1,358-366.
  9. Pranamika Kakati (2013). "A Study on Similarity Measure for Fuzzy Sets" International Journal of Advanced Research in Computer Science and Softaware Engineering, vol. 3 Issue 8, pp. 97-103, August 2013.
  10. Pranamika Kakati (2013) "A New Similarity Measure for Fuzzy Sets with the Extended Definition of Complementation"International Journal of Soft Computing and Engineering, Volume 3 Issue 4, pp. 203-207, September, 2013.
  11. Pranamika Kakati (2013) "A Note on the New Similarity Measure for Fuzzy sets" International Journal of Computer Applications Technology and Research, Volume 2 Issue 5, pp. 601-605, September-October, 2013.
  12. Pranamika Kakati (2013) " A New Architecture of Simplified Fuzzy ARTMAP with the Extended Definition of Complementation" International Journal of Computer Technology and Applications, Volume 4 Issue 5, pp. 772-784, September-October, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy set Complement of a Fuzzy set Fuzzy membership value Fuzzy membership function Fuzzy reference function Similarity measure Medical Diagnostic reasoning.

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