scholarly journals Improved correlation coe_cients of quadripartitioned neutrosophic pythagorean sets for madm

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Radha R ◽  
Stanis Arul Mary A
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Sets ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making

Quadripartitioned single valued Neutrosophic Pythagorean Sets is a improvisation of Wang's single valued neutrosophic sets. In this paper we have studied. The improved correlation coefficient of Quadripartitioned Neutrosophic Pythagorean Sets and investigate it's properties. Further,we have applied the concept of multi attribute decision making methods with quadripartitioned neutrosophic pythagorean environment. Finally we illustrated an example with above proposed method to the multiple attribute decision making problems

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 Possibility Neutrosophic Cubic Sets and Their Application to Multiple Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 269 ◽  
Author(s):  
Huiling Xue ◽  
Xiaotong Yang ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Binary Operation ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Membership Degree ◽  
Neutrosophic Sets ◽  
Important Indicator ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

The neutrosophic cubic sets are an extension of the cubic sets to the neutrosophic sets. It contains three variables, which respectively represent the membership degree, non-membership degree and uncertainty of the element to the set. The score function is an important indicator in the multi-attribute decision-making problem. In this paper, we consider the possibility that an element belongs to a set and put forward the concept of possibility neutrosophic cubic sets. On this basis, we introduce some related concepts and give the binary operation of possibility neutrosophic cubic sets and use specific examples to supplement the corresponding definition. Meanwhile, a decision-making method based on the score function of possibility neutrosophic cubic sets is proposed and a numerical example is given to illustrate the effectiveness of the proposed method.

Set Pair Analysis Method of Containing Target Constraint Mixed Interval Multi-Attribute Decision-Making

2012 ◽  
Vol 226-228 ◽  
pp. 2222-2226 ◽  
Author(s):  
Wen Sheng Lü ◽  
Bin Zhang
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Set Pair Analysis ◽  
Analysis Theory ◽  
Multiple Attribute ◽  
Complex Decision Making ◽  
Multi Attribute Decision Making ◽  
Interval Type ◽  
Pair Analysis ◽  
Attribute Value

In view of target attribute value for different sector number, moreover, also attaches a target constraint condition kind of mix sector multi-attribute decision making question, this paper presents set pair analysis decision-making method. Firstly this paper puts forward three typical interval type attribute value representation; Then using set pair analysis theory, the interval type attribute value unified convert the correlate form, Finally has given complex decision-making criterion function, which collected Conformity degree criteria and Criteria for membership degree. Through the construction plan changes decision-making example analysis shows that this method is a simple and effective method for solving multiple attribute decision making.

scholarly journals A Novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1322
Author(s):  
Yaqing Kou ◽  
Xue Feng ◽  
Jun Wang
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Entropy Measure ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Special Cases ◽  
Multi Attribute Decision Making ◽  
Novel Method ◽  
And Performance

In this paper, a new multiple attribute decision-making (MADM) method under q-rung dual hesitant fuzzy environment from the perspective of aggregation operators is proposed. First, some aggregation operators are proposed for fusing q-rung dual hesitant fuzzy sets (q-RDHFSs). Afterwards, we present properties and some desirable special cases of the new operators. Second, a new entropy measure for q-RDHFSs is developed, which defines a method to calculate the weight information of aggregated q-rung dual hesitant fuzzy elements. Third, a novel MADM method is introduced to deal with decision-making problems under q-RDHFSs environment, wherein weight information is completely unknown. Finally, we present numerical example to show the effectiveness and performance of the new method. Additionally, comparative analysis is conducted to prove the superiorities of our new MADM method. This study mainly contributes to a novel method, which can help decision makes select optimal alternatives when dealing with practical MADM problems.

A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information

2020 ◽  
Vol 19 (01) ◽  
pp. 343-358 ◽  
Author(s):  
Shouzhen Zeng ◽  
Dandan Luo ◽  
Chonghui Zhang ◽  
Xingsen Li
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Set ◽  
Significant Feature ◽  
Multiple Attribute ◽  
Order Preference ◽  
Topsis Approach ◽  
Topsis Model

The single-valued neutrosophic set (SVNS) is considered as an attractive tool for handling highly uncertain and vague information. With this regard, different from the most current distance-based technique for order preference by similarity to ideal solution (TOPSIS) methods, this study proposes a correlation-based TOPSIS model for addressing the single-valued neutrosophic (SVN) multiple attribute decision making (MADM) problems. To achieve this aim, we first develop a novel conception of SVN correlation coefficient, whose significant feature is that it lies in the interval [[Formula: see text],1], which is in accordance with the classical correlation coefficient in statistics, whereas all the existing SVN correlation coefficients in the literature are within unit interval [0,1]. Afterwards, a weighted SVN correlation coefficient is also introduced to infuse the importance of attributes. Moreover, a correlation-based comprehensive index is further proposed to establish the central structure of TOPSIS model, called the SVN correlation-based TOPSIS approach. Finally, a numerical example and relevant comparative analysis are implemented to explain the applicability and effectiveness of the mentioned methodology.

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