Design Gaussian information granule based on the principle of justifiable granularity: A multi-dimensional perspective

被引：9
|
作者：
Wang, Degang [1 ,2 ]
Liu, Hao [1 ,2 ]
Pedrycz, Witold [3 ]
Song, Wenyan [4 ]
Li, Hongxing [1 ,2 ]
机构：
[1] Dalian Univ Technol, Minist Educ, Key Lab Intelligent Control & Optimizat Ind Equip, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[3] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1H9, Canada
[4] Dongbei Univ Finance & Econ, Sch Econ, Dalian 116025, Peoples R China
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2022年 / 197卷
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
Information granule; Principle of justifiable granularity; Inhibitory data; Correlation; Confidence level; FUZZY-SETS; CLASSIFIERS; MODEL;
D O I：
10.1016/j.eswa.2022.116763
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this study, based on the principle of justifiable granularity, a method for designing multi-dimensional information granules is proposed. To design information granules, the correlations among the different variables within the data and their confidence levels are considered. The designed information granules reveal the relationships present in the experimental data and help to capture more features of the original data. In addition, a strategy for the exclusion of inhibitory data is considered, making the design of information granules more focused. Several experimental studies are conducted to quantify the effectiveness of the proposed method.
引用
收藏
页数：13
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