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Information 2017, 8(4), 162; https://doi.org/10.3390/info8040162

Some New Biparametric Distance Measures on Single-Valued Neutrosophic Sets with Applications to Pattern Recognition and Medical Diagnosis

School of Mathematics, Thapar Institute of Engineering & Technology, Deemed University Patiala, Punjab 147004, India
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Received: 29 November 2017 / Revised: 10 December 2017 / Accepted: 11 December 2017 / Published: 15 December 2017
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)
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Abstract

Single-valued neutrosophic sets (SVNSs) handling the uncertainties characterized by truth, indeterminacy, and falsity membership degrees, are a more flexible way to capture uncertainty. In this paper, some new types of distance measures, overcoming the shortcomings of the existing measures, for SVNSs with two parameters are proposed along with their proofs. The various desirable relations between the proposed measures have also been derived. A comparison between the proposed and the existing measures has been performed in terms of counter-intuitive cases for showing its validity. The proposed measures have been illustrated with case studies of pattern recognition as well as medical diagnoses, along with the effect of the different parameters on the ordering of the objects. View Full-Text
Keywords: decision-making; single-valued neutrosophic sets; distance measure; pattern recognition; uncertainties decision-making; single-valued neutrosophic sets; distance measure; pattern recognition; uncertainties
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Garg, H.; Nancy. Some New Biparametric Distance Measures on Single-Valued Neutrosophic Sets with Applications to Pattern Recognition and Medical Diagnosis. Information 2017, 8, 162.

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