Hybrid vector similarity measure of single valued refined neutrosophic sets to multi-attribute decision making problems
Surapati Pramanik · Partha Pratim Dey · Bibhas C. Giri
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About this ebook
This paper proposes hybrid vector similarity measures under single valued refined neutrosophic sets
and proves some of its basic properties. The proposed similarity measure is then applied for solving
multiple attribute decision making problems. Lastly, a numerical example of medical diagnosis is
given on the basis of the proposed hybrid similarity measures and the results are compared with the
results of other existing methods to validate the applicability, simplicity and effectiveness of the
proposed method.
and proves some of its basic properties. The proposed similarity measure is then applied for solving
multiple attribute decision making problems. Lastly, a numerical example of medical diagnosis is
given on the basis of the proposed hybrid similarity measures and the results are compared with the
results of other existing methods to validate the applicability, simplicity and effectiveness of the
proposed method.
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