نتایج جستجو برای: single valued neutrosophic set
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In this paper, we present multi-attribute decision-making problem with neutrosophic assessment. We assume that the information about attribute weights is incompletely known or completely unknown. The ratings of alternatives with respect to each attributes are considered as single-valued neutrosophic set to catch up imprecise or vague information. Neutrosophic set is characterized by three indep...
An interval neutrosophic set (INS) is a subclass of a neutrosophic set and a generalization of an interval-valued intuitionistic fuzzy set, and then the characteristics of INS are independently described by the interval numbers of its truth-membership, indeterminacy-membership, and falsity-membership degrees. However, the exponential parameters (weights) of all the existing exponential operatio...
This paper presents rough netrosophic multiattribute decision making based on grey relational analysis. While the concept of neutrosophic sets is a powerful logic to deal with indeterminate and inconsistent data, the theory of rough neutrosophic sets is also a powerful mathematical tool to deal with incompleteness. The rating of all alternatives is expressed with the upper and lower approximati...
The paper presents the correlation and correlation coefficient of single-valued neutrosophic sets (SVNSs) based on the extension of the correlation of intuitionistic fuzzy sets and demonstrates that the cosine similarity measure is a special case of the correlation coefficient in SVNS. Then a decision-making method is proposed by the use of the weighted correlation coefficient or the weighted c...
The use of a single-valued neutrosophic set (svns) makes it much easier to manage situations in which one must deal with incorrect, unexpected, susceptible, faulty, vulnerable, and complicated information. This is result the fact that specific forms material being discussed here are more likely include errors. new theory has directly contributed expansion both concept fuzzy sets intuitionistic ...
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