Another view on knowledge measures in atanassov intuitionistic fuzzy sets

被引：5

作者：

Ali, Muhammad Irfan ^{[1
]}

Zhan, Jianming ^{[2
]}

Khan, Muhammad Jabir ^{[3
]}

Mahmood, Tahir ^{[4
]}

Faizan, Haider ^{[4
]}

机构：

[1] Islamabad Model Coll Boys, F-10-3, Islamabad, Pakistan

[2] Hubei Univ Nationalities, Dept Math, Enshi 445000, Hubei, Peoples R China

[3] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Dept Math, SCL 802 Fixed Point Lab,KMUTT Fixed Point Res Lab, 126 Pracha Uthit Rd, Bangkok 10140, Thailand

[4] Int Islamic Univ Islamabad, Dept Math & Stat, Islamabad, Pakistan

来源：

SOFT COMPUTING | 2022年 / 26卷 / 14期

关键词：

Fuzzy sets; Intuitionistic fuzzy sets; Entropy; Uncertainty index; Knowledge measure; DECISION-MAKING; ENTROPY; AGGREGATION; INFORMATION; RANKING;

D O I：

10.1007/s00500-022-07127-3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Information quantification in numerical form for any given data is very useful in decision-making problems. In Atanassov intuitionistic fuzzy sets (A-IFSs), such quantification becomes more important due to uncertainties such as intuitionism and fuzziness. Distribution of these uncertainties is a key to determine knowledge associated with Atanassov intuitionistic values (A-IFVs). In this paper, first distribution of the above-mentioned uncertainties and their relationship are discussed. Then, knowledge measures are defined as a function of entropy and uncertainty index, with certain desired properties. Existence of such knowledge measures has been established. Further, it is shown that how proposed knowledge measures are useful in multi-criteria group decision-making (MCGDM) problems.

引用

页码：6507 / 6517

页数：11

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