New Similarity Measures of Simplified Neutrosophic Sets and Their Applications


Chunfang Liu, Journal of Information Processing Systems Vol. 14, No. 3, pp. 790-800, Jun. 2018  

https://doi.org/10.3745/JIPS.04.0078
Keywords: Multi-Criteria Decision-Making, Pattern Recognition, Similarity Measure, Simplified Neutrosophic Sets
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Abstract

The simplified neutrosophic set (SNS) is a generalization of fuzzy set that is designed for some practical situations in which each element has truth membership function, indeterminacy membership function and falsity membership function. In this paper, we propose a new method to construct similarity measures of single valued neutrosophic sets (SVNSs) and interval valued neutrosophic sets (IVNSs), respectively. Then we prove that the proposed formulas satisfy the axiomatic definition of the similarity measure. At last, we apply them to pattern recognition under the single valued neutrosophic environment and multi-criteria decisionmaking problems under the interval valued neutrosophic environment. The results show that our methods are effective and reasonable.


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Cite this article
[APA Style]
Liu, C. (2018). New Similarity Measures of Simplified Neutrosophic Sets and Their Applications. Journal of Information Processing Systems, 14(3), 790-800. DOI: 10.3745/JIPS.04.0078.

[IEEE Style]
C. Liu, "New Similarity Measures of Simplified Neutrosophic Sets and Their Applications," Journal of Information Processing Systems, vol. 14, no. 3, pp. 790-800, 2018. DOI: 10.3745/JIPS.04.0078.

[ACM Style]
Chunfang Liu. 2018. New Similarity Measures of Simplified Neutrosophic Sets and Their Applications. Journal of Information Processing Systems, 14, 3, (2018), 790-800. DOI: 10.3745/JIPS.04.0078.