A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition

被引：86
作者：
Zhang, Zhenhua [1 ]
Wang, Min [1 ]
Hu, Yong [2 ]
Yang, Jingyu [3 ]
Ye, Youpei [3 ]
Li, Yafang [4 ]
机构：
[1] Guangdong Univ Foreign Studies, Cisco Sch Informat, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Univ Foreign Studies, Sch Management, Guangzhou, Guangdong, Peoples R China
[3] Nanjing Univ Sci & Technol, Sch Comp Sci & Technol, Nanjing, Jiangsu, Peoples R China
[4] Southern Med Univ, Affiliated Hosp 1, Lab Reprod Med, Guangzhou, Guangdong, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2013年 / 2013卷
基金：
中国国家自然科学基金;
关键词：
SIMILARITY MEASURES; DOUBLE PARAMETERS; DISTANCES;
D O I：
10.1155/2013/408012
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
We present dynamic interval-valued intuitionistic fuzzy sets (DIVIFS), which can improve the recognition accuracy when they are applied to pattern recognition. By analyzing the degree of hesitancy, we propose some DIVIFS models from intuitionistic fuzzy sets (IFS) and interval-valued IFS (IVIFS). And then we present a novel ranking condition on the distance of IFS and IVIFS and introduce some distance measures of DIVIFS satisfying the ranking condition. Finally, a pattern recognition example applied to medical diagnosis decision making is given to demonstrate the application of DIVIFS and its distances. The simulation results show that the DIVIFS method is more comprehensive and flexible than the IFS method and the IVIFS method.
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页数：16
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