A new multi-criteria decision making algorithm for medical diagnosis and classification problems using divergence measure of picture fuzzy sets

被引:21
|
作者
Nguyen Xuan Thao [1 ]
Ali, Mumtaz [2 ]
Le Thi Nhung [1 ]
Gianey, Hemant Kumar [3 ]
Smarandache, Florentin [4 ]
机构
[1] Vietnam Natl Univ Agr, Hanoi, Vietnam
[2] Deakin Univ, Sch Informat Technol, 2Deakin SWU Joint Res Ctr Big Data, Geelong, Vic, Australia
[3] Thapar Inst Engn & Technol, Patiala, Punjab, India
[4] Univ New Mexico, Math Dept, Gallup, NM USA
关键词
Picture fuzzy set; picture fuzzy divergence measure; medical diagnosis; classification problem; AGGREGATION OPERATORS; ENTROPY; MODELS; (I;
D O I
10.3233/JIFS-182697
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A divergence measure plays an important part in distinguishing two probability distributions and drawing conclusions based on that discrimination. In this paper, we proposed the concept of divergence measure of picture fuzzy sets. We also built some formulas of the proposed divergence measure of picture fuzzy sets anddiscussed some basic properties of this measure.Based on the proposedmeasure, we developed a multi-criteria decision-making algorithm. Finally, we applied the proposed multi-criteria decision-making algorithm in the medical diagnosis problem and the classification problem.
引用
收藏
页码:7785 / 7796
页数:12
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