Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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New Similarity Measures of Simplified Neutrosophic Sets and Their Applications

  • Liu, Chunfang (College of Science, Northeast Forestry University)
  • Received : 2015.08.07
  • Accepted : 2017.04.16
  • Published : 2018.06.30
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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 decision-making problems under the interval valued neutrosophic environment. The results show that our methods are effective and reasonable.

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