Uncertainty measures of interval-valued intuitionistic fuzzy soft sets and their applications in decision making

2017 ◽  
Vol 21 (1) ◽  
pp. 77-95 ◽  
Author(s):  
Qinrong Feng ◽  
Xiao Guo
Keyword(s):  
Decision Making ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Uncertainty Measures ◽  
Fuzzy Soft Sets ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

An Adjustable Reduction Approach of Interval-valued Intuitionistic Fuzzy Soft Sets for Decision Making

2017 ◽  
Vol 11 (4) ◽  
pp. 999-1009 ◽  
Author(s):  
Hongwu Qin ◽  
Ahmad ShukriMohd Noor ◽  
Xiuqin Ma ◽  
Haruna Chiroma ◽  
Tutut Herawan
Keyword(s):  
Decision Making ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets ◽  
Reduction Approach

scholarly journals APPLICATION OF INTERVAL VALUED INTUITIONISTIC FUZZY SOFT SETS OF ROOT TYPE IN DECISION MAKING

2016 ◽  
Vol 06 (03) ◽  
pp. 1224-1230 ◽  
Author(s):  
Anita Shanthi S ◽  
◽  
Thillaigovindan N ◽  
Vadivel Naidu J ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

scholarly journals TOPSIS Method Based on the Correlation Coefficient of Interval-Valued Intuitionistic Fuzzy Soft Sets and Aggregation Operators with Their Application in Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Rana Muhammad Zulqarnain ◽  
Xiao Long Xin ◽  
Muhammad Saqlain ◽  
Waseem Asghar Khan
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Weighted Average ◽  
Correlation Coefficients ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets ◽  
Weighted Correlation

The correlation coefficient between the two parameters plays a significant part in statistics. Furthermore, the exactness of the assessment of correlation depends upon information from the set of discourses. The data collected for various statistical studies are full of ambiguities. The idea of interval-valued intuitionistic fuzzy soft sets is an extension of intuitionistic fuzzy soft sets that is used to express insufficient evaluation, uncertainty, and anxiety in decision-making. Intuitionistic fuzzy soft sets consider two different types of information, such as membership degree and nonmembership degree. In this paper, the concepts and properties of the correlation coefficient and the weighted correlation coefficient of interval-valued intuitionistic fuzzy soft sets are proposed. A prioritization technique for order preference by similarity to the ideal solution based on interval-valued intuitionistic fuzzy soft sets of correlation coefficients and the weighted correlation coefficient is introduced. We also proposed interval-valued intuitionistic fuzzy soft weighted average and interval-valued intuitionistic fuzzy soft weighted geometric operators and developed decision-making techniques based on the proposed operators. By using the developed techniques, a method for solving decision-making problems is proposed. To ensure the applicability of the proposed methods, an illustrative example is given. Finally, we present a comparison of some existing methods with our proposed techniques.

Generalized interval-valued hesitant intuitionistic fuzzy soft sets

2021 ◽  
pp. 1-12
Author(s):  
Admi Nazra ◽  
Yudiantri Asdi ◽  
Sisri Wahyuni ◽  
Hafizah Ramadhani ◽  
Zulvera
Keyword(s):  
Hesitant Fuzzy Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Binary Operations ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Comparison Table ◽  
Definition Of ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

This paper aims to extend the Interval-valued Intuitionistic Hesitant Fuzzy Set to a Generalized Interval-valued Hesitant Intuitionistic Fuzzy Soft Set (GIVHIFSS). Definition of a GIVHIFSS and some of their operations are defined, and some of their properties are studied. In these GIVHIFSSs, the authors have defined complement, null, and absolute. Soft binary operations like operations union, intersection, a subset are also defined. Here is also verified De Morgan’s laws and the algebraic structure of GIVHIFSSs. Finally, by using the comparison table, a different approach to GIVHIFSS based decision-making is presented.

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