An MADM approach to covering-based variable precision fuzzy rough sets: an application to medical diagnosis

被引：50

作者：

Jiang, Haibo ^{[1
]}

Zhan, Jianming ^{[1
]}

Sun, Bingzhen ^{[2
]}

Alcantud, Jose Carlos R. ^{[3
,4
]}

机构：

[1] Hubei Minzu Univ, Dept Math, Enshi 445000, Peoples R China

[2] Xidian Univ, Sch Econ & Management, Xian 710071, Peoples R China

[3] Univ Salamanca, BORDA Res Unit, Salamanca 37007, Spain

[4] Univ Salamanca, Multidisciplinary Inst Enterprise IME, Salamanca 37007, Spain

来源：

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2020年 / 11卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Covering-based variable precision fuzzy rough set; Fuzzy neighborhood operator; Fuzzy logical operator; Multi-attribute decision-making; Medicine selection problem; CRITERIA DECISION-MAKING; TOPSIS METHOD; 3-WAY DECISIONS; OPERATORS; MODELS; VIKOR; (I;

D O I：

10.1007/s13042-020-01109-3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In medical diagnosis, how to select an optimal medicine from some medicines with similar efficacy values to treat diseases has become common problems between doctors and patients. To solve this problem, we describe it as a multi-attribute decision-making (MADM) in a finite fuzzy covering approximation space. This paper aims to propose two pairs of covering-based variable precision fuzzy rough sets. By combining the proposed rough set model with the VIKOR method, we construct a novel method to medicine selection MADM problems in the context of medical diagnosis. A real-life case study of selecting a proper medicine to treat Alzheimer's disease is given to demonstrate the practicality of our proposed method. Through a comparative analysis and an experimental analysis, we further explore the effectiveness and stability of the established method.

引用

页码：2181 / 2207

页数：27

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