A new ranking technique for q-rung orthopair fuzzy values

被引：33
作者：
Khan, Muhammad Jabir [1 ,2 ]
Ali, Muhammad Irfan [3 ]
Kumam, Poom [1 ,2 ,4 ]
机构：
[1] King Mongkuts Univ Technol Thonburi KMUTT, Dept Math, KMUTT Fixed Point Res Lab, Fac Sci, Sci Lab Bldg,126 Pracha Uthit Rd, Bangkok 10140, Thailand
[2] King Mongkuts Univ Technol Thonburi KMUTT, Ctr Excellence Theoret & Computat Sci TaCS CoE, SCL Fixed Point Lab 802, Bangkok, Thailand
[3] Islamabad Model Coll Girls, Dept Math, Islamabad, Pakistan
[4] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
来源：
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS | 2021年 / 36卷 / 01期
关键词：
entropy; knowledge base; qROFS; ranking techniques; MUIRHEAD MEAN OPERATORS; SOFT SET; ENTROPY; VIEW;
D O I：
10.1002/int.22311
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In intuitionistic fuzzy set and their generalizations such as Pythagorean fuzzy sets and q-rung orthopair fuzzy sets, ranking is not easy to define. There are several techniques available in literature for ranking values in above mentioned orthopair fuzzy sets. It is interesting to see that almost all the proposed ranking methods produce distinct ranking. Notion of knowledge base is very important to study ranking proposed by different techniques. Aim of this paper is to critically analyze the available ranking techniques for q-rung orthopair fuzzy values and propose a new graphical ranking method based on hesitancy index and entropy. Several numerical examples are tested with the proposed technique, which shows that the technique is intuitive and convenient for real life applications.
引用
收藏
页码：558 / 592
页数：35
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