A New Similarity Measure of Generalized Fuzzy Numbers Based on Geometric-mean Averaging Operator

Author(s):  
Shi-Jay Chen
2019 ◽  
Vol 8 (4) ◽  
pp. 1232-1238
Author(s):  
Daud Mohamad ◽  
Noorlisa Sara Adlene Ramlan ◽  
Sharifah Aniza Sayed Ahmad

Similarity measure between two fuzzy sets is an important tool for comparing various characteristics of the fuzzy sets. It is a preferred approach as compared to distance methods as the defuzzification process in obtaining the distance between fuzzy sets will incur loss of information. Many similarity measures have been introduced but most of them are not capable to discriminate certain type of fuzzy numbers. In this paper, an improvised similarity measure for generalized fuzzy numbers that incorporate several essential features is proposed. The features under consideration are geometric mean averaging, Hausdorff distance, distance between elements, distance between center of gravity and the Jaccard index. The new similarity measure is validated using some benchmark sample sets. The proposed similarity measure is found to be consistent with other existing methods with an advantage of able to solve some discriminant problems that other methods cannot. Analysis of the advantages of the improvised similarity measure is presented and discussed. The proposed similarity measure can be incorporated in decision making procedure with fuzzy environment for ranking purposes.


2011 ◽  
Vol 15 ◽  
pp. 2773-2777 ◽  
Author(s):  
Jiang Wen ◽  
Xin Fan ◽  
Dejie Duanmu ◽  
Deng Yong

2012 ◽  
Vol 21 (S1) ◽  
pp. 289-294 ◽  
Author(s):  
T. Allahviranloo ◽  
S. Abbasbandy ◽  
S. Hajighasemi

2010 ◽  
Vol 159 ◽  
pp. 393-398
Author(s):  
Chun Jiang Zhao

A modified method to measure the similarity between the generalized fuzzy numbers based on Wasserstein distance is proposed. The method is more fully considered the difference of the generalized fuzzy numbers, especially the shape difference, by Wasserstein distance. The results of comparing the eighteen sets of generalized fuzzy numbers show that the method can overcome the drawbacks of the existing methods, and calculate the similarity measure excellently.


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