Uncertainty measurement for a fuzzy set-valued information system

被引：5

作者：

Li, Zhaowen ^{[1
]}

Wang, Zhihong ^{[2
]}

Li, Qingguo ^{[3
]}

Wang, Pei ^{[1
]}

Wen, Ching-Feng ^{[4
]}

机构：

[1] Yulin Normal Univ, Dept Guangxi Educ, Key Lab Complex Syst Optimizat & Big Data Proc, Yulin 537000, Guangxi, Peoples R China

[2] Guangxi Univ Nationalities, Sch Math & Phys, Nanning 530006, Guangxi, Peoples R China

[3] Hunan Univ, Sch Math & Econometr, Changsha 410082, Hunan, Peoples R China

[4] Kaohsiung Med Univ, Res Ctr Nonlinear Anal & Optimizat, Ctr Fundamental Sci, Dept Med Res, Kaohsiung 80708, Taiwan

来源：

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2021年 / 12卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Fuzzy set; FSVIS; Information structure; Uncertainty; Measurement; Effectiveness; KNOWLEDGE GRANULATION; ROUGH ENTROPY;

D O I：

10.1007/s13042-020-01273-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Uncertainty measurement (UM) can offer new visual angle for data analysis. A fuzzy set-valued information system (FSVIS) which means an information system (IS) where its information values are fuzzy sets. This article investigates UM for a FSVIS. First, a FSVIS is introduced. Then, the distance between two information values of each attribute in a FSVIS is founded. After that, the tolerance relation induced by a given subsystem is acquired by this distance. Moreover, the information structure of this subsystem is brought forward. Additionally, measures of uncertainty for a FSVIS are explored. Eventually, to verify the validity of these measures, statistical effectiveness analysis is carried out. The obtained results will help us understand the intrinsic properties of uncertainty in a FSVIS.

引用

页码：1769 / 1787

页数：19

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