Inclusion measure and its use in measuring similarity and distance measure between hesitant fuzzy sets

2013 ◽  
Author(s):  
Shu Yun Yang ◽  
Hong Ying Zhang ◽  
Zhi Wei Yue
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Hesitant Fuzzy Sets ◽  
Inclusion Measure

scholarly journals A Consistency Check Method for Trusted Hesitant Fuzzy Sets with Confidence Levels Based on a Distance Measure

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Huimin Xiao ◽  
Meiqi Wang ◽  
Xiaoning Xi
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Consistency Check ◽  
Hesitant Fuzzy Sets ◽  
Numerical Examples ◽  
Confidence Levels ◽  
Check Method ◽  
The Difference

This paper proposes a consistency check method for hesitant fuzzy sets with confidence levels by employing a distance measure. Firstly, we analyze the difference between each fuzzy element and its corresponding attribute comprehensive decision value and then obtain a comprehensive distance measure for each attribute. Subsequently, by taking the relative credibility as the weight, we assess the consistency of hesitant fuzzy sets. Finally, numerical examples are put forward to verify the effectiveness and reliability of the proposed method.

scholarly journals Interval Entropy of Fuzzy Sets and the Application to Fuzzy Multiple Attribute Decision Making

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yiying Shi ◽  
Xuehai Yuan
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Distance Measure ◽  
Multiple Attribute Decision Making ◽  
Inclusion Measure ◽  
New Concepts ◽  
Multiple Attribute ◽  
Interval Distance ◽  
Set Up ◽  
Interval Inclusion

A series of new concepts including interval entropy, interval similarity measure, interval distance measure, and interval inclusion measure of fuzzy sets are introduced. Meanwhile, some theorems and corollaries are proposed to show how these definitions can be deduced from each other. And then, based on interval entropy, a fuzzy multiple attribute decision making (FMADM) model is set up. In this model, interval entropy is used as the weight, by which the evaluation values of all alternatives can be obtained. Then all alternatives with respect to each criterion can be ranked as the order of the evaluation values. At last, a practical example is given to illustrate an application of the developed model and a comparative analysis is made.

scholarly journals Modelling Uncertainties in Multi-Criteria Decision Making using Distance Measure and TOPSIS for Hesitant Fuzzy Sets

2017 ◽  
Vol 7 (2) ◽  
pp. 103-109 ◽  
Author(s):  
Ismat Beg ◽  
Tabasam Rashid
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Distance Measure ◽  
Fuzzy Data ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Hesitant Fuzzy Sets ◽  
New Approach ◽  
Order Preference ◽  
Modelling Uncertainties

Abstract A notion for distance between hesitant fuzzy data is given. Using this new distance notion, we propose the technique for order preference by similarity to ideal solution for hesitant fuzzy sets and a new approach in modelling uncertainties. An illustrative example is constructed to show the feasibility and practicality of the new method.

Note on distance measure of hesitant fuzzy sets

2015 ◽  
Vol 321 ◽  
pp. 103-115 ◽  
Author(s):  
Deqing Li ◽  
Wenyi Zeng ◽  
Yibin Zhao
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Hesitant Fuzzy Sets

A new multi-criteria decision-making method utilizing power heronian operators with picture hesitant fuzzy information

2021 ◽  
pp. 1-22
Author(s):  
Baolin Li ◽  
Lihua Yang ◽  
Jie Qian
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Numbers ◽  
Distance Measure ◽  
Multi Criteria Decision Making ◽  
Comparison Analysis ◽  
Fuzzy Information ◽  
Hesitant Fuzzy Sets ◽  
Novel Method ◽  
Picture Fuzzy Sets

In practice, picture hesitant fuzzy sets (PHFSs) combining the picture fuzzy sets (PFSs) and hesitant fuzzy sets (HFSs) are suitable to represent more complex multi-criteria decision-making (MCDM) information. The power heronian (PH) operators, which have the merits of power average (PA) and heronian mean (HM) operators, are extended to the environment of PHFSs in this article. First, some algebraic operations of picture hesitant fuzzy numbers (PHFNs), comparative functions and distance measure are introduced. Second, two novel operators, called as picture hesitant fuzzy weighted power heronian (PHFWPH) operator and picture hesitant fuzzy weighted geometric power heronian (PHFWGPH) operator, are defined. Meanwhile, some desirable characteristics and special instances of two operators are investigated as well. Third, a novel MCDM approach applying the proposed PH operators to handle PHFNs is explored. Lastly, to indicate the effectiveness of this novel method, an example regarding MCDM problem is conducted, as well as sensitivity and comparison analysis.

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