scholarly journals Vector Similarity Measures between Refined Simplified Neutrosophic Sets and Their Multiple Attribute Decision-Making Method

Symmetry ◽  
2017 ◽  
Vol 9 (8) ◽  
pp. 153 ◽  
Author(s):  
Jiqian Chen ◽  
Jun Ye ◽  
Shigui Du
Keyword(s):  
Decision Making ◽  
Similarity Measures ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Sets ◽  
Multiple Attribute

Improved Correlation Coefficients of Quadripartitioned Single-Valued Neutrosophic Sets and Interval-Quadripartitioned Neutrosophic Sets

2020 ◽  
pp. 331-363
Author(s):  
Mohanasundari M. ◽  
Mohana K.
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Sets ◽  
Statistical Measures ◽  
Multiple Attribute

A correlation coefficient is one of the statistical measures that helps to find the degree of changes to the value of one variable predict change to the value of another. Quadripartitioned single valued neutrosophic sets is an improvization of Wang's single valued neutrosophic sets. This chapter deals the improved correlation coefficients of quadripartitioned single valued neutrosophic sets, interval quadripartitioned neutrosophic sets, and investigates its properties. And this concept is also applied in multiple-attribute decision-making methods with quadripartitioned single valued neutrosophic environment and interval quadripartitioned neutrosophic environment. Finally an illustrated example is given in the proposed method to the multiple-attribute decision-making problems.

Correlation Coefficients of Refined-Single Valued Neutrosophic Sets and Their Applications in Multiple Attribute Decision-Making

2019 ◽  
Vol 23 (3) ◽  
pp. 421-426 ◽  
Author(s):  
Changxing Fan ◽  
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Sets ◽  
Actual Application ◽  
Multiple Attribute ◽  
Weighted Correlation ◽  
The Ideal

The paper presents the correlation coefficient of refined-single valued neutrosophic sets (Refined-SVNSs) based on the extension of the correlation of single valued neutrosophic sets (SVNSs), and then a decision making method is proposed by the use of the weighted correlation coefficient of Refined-SVNSs. Through the weighted correlation coefficient between the ideal alternative and each alternative, we can rank all alternatives and the best one of all alternatives can be easily identified as well. Finally, to prove this decision making method proposed in this paper is useful to deal with the actual application, we use an example to illustrate it.

scholarly journals Multiple-Attribute Decision-Making Method Using Similarity Measures of Hesitant Linguistic Neutrosophic Numbers Regarding Least Common Multiple Cardinality

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 330 ◽  
Author(s):  
Wenhua Cui ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Similarity Measures ◽  
Multiple Attribute Decision Making ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Common Multiple ◽  
Least Common Multiple ◽  
Multiple Attribute ◽  
Linguistic Neutrosophic Numbers

Linguistic neutrosophic numbers (LNNs) are a powerful tool for describing fuzzy information with three independent linguistic variables (LVs), which express the degrees of truth, uncertainty, and falsity, respectively. However, existing LNNs cannot depict the hesitancy of the decision-maker (DM). To solve this issue, this paper first defines a hesitant linguistic neutrosophic number (HLNN), which consists of a few LNNs regarding an evaluated object due to DMs’ hesitancy to represent their hesitant and uncertain information in the decision-making process. Then, based on the least common multiple cardinality (LCMC), we present generalized distance and similarity measures of HLNNs, and then develop a similarity measure-based multiple-attribute decision-making (MADM) method to handle the MADM problem in the HLNN setting. Finally, the feasibility of the proposed approach is verified by an investment decision case.

scholarly journals Similarity Measures of q-Rung Orthopair Fuzzy Sets Based on Cosine Function and Their Applications

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 340 ◽  
Author(s):  
Wang ◽  
Wang ◽  
Wei ◽  
Wei
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Similarity Measures ◽  
Multiple Attribute Decision Making ◽  
Membership Degree ◽  
Numerical Examples ◽  
Multiple Attribute ◽  
Cosine Similarity Measures ◽  
Scheme Selection

In this article, we propose another form of ten similarity measures by considering the function of membership degree, non-membership degree, and indeterminacy membership degree between the q-ROFSs on the basis of the traditional cosine similarity measures and cotangent similarity measures. Then, we utilize our presented ten similarity measures and ten weighted similarity measures between q-ROFSs to deal with multiple attribute decision-making (MADM) problems including pattern recognition and scheme selection. Finally, two numerical examples are provided to illustrate the scientific and effective of the similarity measures for pattern recognition and scheme selection.

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