Uncertainty measurement for a fuzzy set-valued information system

被引：0
|
作者：
Zhaowen Li
Zhihong Wang
Qingguo Li
Pei Wang
Ching-Feng Wen
机构：
[1] Yulin Normal University,Key Laboratory of Complex System Optimization and Big Data Processing in Department of Guangxi Education
[2] Guangxi University for Nationalities,School of Mathematics and Physics
[3] Hunan University,School of Mathematics and Econometrics
[4] Kaohsiung Medical University,Department of Medical Research, Center for Fundamental Science, Research Center for Nonlinear Analysis and Optimization
来源：
International Journal of Machine Learning and Cybernetics | 2021年 / 12卷
关键词：
Fuzzy set; FSVIS; Information structure; Uncertainty; Measurement; Effectiveness;
D O I：
暂无
中图分类号：
学科分类号：
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.
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页码：1769 / 1787
页数：18
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