An innovative TOPSIS approach based on hesitant fuzzy correlation coefficient and its applications

2018 ◽  
Vol 68 ◽  
pp. 249-267 ◽  
Author(s):  
Guidong Sun ◽  
Xin Guan ◽  
Xiao Yi ◽  
Zheng Zhou
Keyword(s):  
Correlation Coefficient ◽  
Fuzzy Correlation ◽  
Topsis Approach

Some new Pythagorean fuzzy correlation techniques via statistical viewpoint with applications to decision-making problems

2021 ◽  
pp. 1-13
Author(s):  
Paul Augustine Ejegwa ◽  
Shiping Wen ◽  
Yuming Feng ◽  
Wei Zhang ◽  
Jia Chen
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Superior Performance ◽  
Statistical Techniques ◽  
New Techniques ◽  
Reliable Technique ◽  
Performance Indexes ◽  
Fuzzy Correlation

Pythagorean fuzzy set is a reliable technique for soft computing because of its ability to curb indeterminate data when compare to intuitionistic fuzzy set. Among the several measuring tools in Pythagorean fuzzy environment, correlation coefficient is very vital since it has the capacity to measure interdependency and interrelationship between any two arbitrary Pythagorean fuzzy sets (PFSs). In Pythagorean fuzzy correlation coefficient, some techniques of calculating correlation coefficient of PFSs (CCPFSs) via statistical perspective have been proposed, however, with some limitations namely; (i) failure to incorporate all parameters of PFSs which lead to information loss, (ii) imprecise results, and (iii) less performance indexes. Sequel, this paper introduces some new statistical techniques of computing CCPFSs by using Pythagorean fuzzy variance and covariance which resolve the limitations with better performance indexes. The new techniques incorporate the three parameters of PFSs and defined within the range [-1, 1] to show the power of correlation between the PFSs and to indicate whether the PFSs under consideration are negatively or positively related. The validity of the new statistical techniques of computing CCPFSs is tested by considering some numerical examples, wherein the new techniques show superior performance indexes in contrast to the similar existing ones. To demonstrate the applicability of the new statistical techniques of computing CCPFSs, some multi-criteria decision-making problems (MCDM) involving medical diagnosis and pattern recognition problems are determined via the new techniques.

scholarly journals EVALUATION OF HOTEL QUALITY ATTRIBUTE IMPORTANCE THROUGH FUZZY CORRELATION COEFFICIENT

2016 ◽  
Vol 22 (4) ◽  
pp. 471-492 ◽  
Author(s):  
Olimpia-Iuliana BAN ◽  
Ioan Gheorghe TARA ◽  
Victoria BOGDAN ◽  
Delia TUŞE ◽  
Simona Gabriela BOLOGA
Keyword(s):  
Correlation Coefficient ◽  
Indirect Method ◽  
Fuzzy Numbers ◽  
Quality Attribute ◽  
Triangular Fuzzy Numbers ◽  
Attribute Importance ◽  
Method Of Calculation ◽  
Fuzzy Correlation

An indirect method of calculation of the importance of attributes as the fuzzy correlation between the performance of attributes and the overall satisfaction was proposed in a recent paper. We apply the method to the results of a survey with respect to the quality of hotel services in Oradea (Romania). Different representations of the answers as triangular fuzzy numbers, as well as distinct analyzes to compare the hierarchies of the attributes with respect to the experience with the hotel and the motivation of the travel are considered.

scholarly journals A Multi-Attribute Pearson’s Picture Fuzzy Correlation-Based Decision-Making Method

Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 999 ◽  
Author(s):  
Jin ◽  
Wu ◽  
Sun ◽  
Zeng ◽  
Luo ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Correlation Coefficient ◽  
Ideal Point ◽  
New Correlation ◽  
Fuzzy Correlation ◽  
Relative Proximity ◽  
Fuzzy Madm ◽  
Multi Attribute Decision Making ◽  
Picture Fuzzy Sets

As a generalization of several fuzzy tools, picture fuzzy sets (PFSs) hold a special ability to perfectly portray inherent uncertain and vague decision preferences. The intention of this paper is to present a Pearson’s picture fuzzy correlation-based model for multi-attribute decision-making (MADM) analysis. To this end, we develop a new correlation coefficient for picture fuzzy sets, based on which a Pearson’s picture fuzzy closeness index is introduced to simultaneously calculate the relative proximity to the positive ideal point and the relative distance from the negative ideal point. On the basis of the presented concepts, a Pearson’s correlation-based model is further presented to address picture fuzzy MADM problems. Finally, an illustrative example is provided to examine the usefulness and feasibility of the proposed methodology.

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.

scholarly journals Enhancing the Long-Term Yield Competitiveness of a Semiconductor Manufacturing Factory Using a Multiobjective Fuzzy Nonlinear Programming Approach

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Toly Chen ◽  
Yi-Chi Wang
Keyword(s):  
Nonlinear Programming ◽  
Correlation Coefficient ◽  
Semiconductor Manufacturing ◽  
Programming Approach ◽  
Manufacturing Plant ◽  
Systematic Procedure ◽  
Fuzzy Correlation ◽  
Proposed Model ◽  
Fuzzy Nonlinear Programming

This study proposes a multiobjective fuzzy nonlinear programming (MOFNP) approach to enhance the long-term yield competitiveness of a semiconductor manufacturing factory. By modeling the long-term competitiveness of every product in a semiconductor manufacturing plant with the fuzzy correlation coefficient (FCC) between time and instantaneous competitiveness, the proposed model considers the various viewpoints when interpreting the overall competitiveness of the semiconductor manufacturing plant in the long-term. All noninferior solutions of the MOFNP solutions are then derived using a systematic procedure. A real example is employed to illustrate the applicability of the proposed methodology.

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