Distance Measure of Hesitant Fuzzy Sets and its Application in Image Segmentation

被引：5
|
作者：
Zeng, Wenyi [1 ]
Ma, Rong [1 ]
Li, Deqing [1 ,2 ]
Yin, Qian [1 ]
Xu, Zeshui [3 ]
机构：
[1] Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China
[2] Neusoft Inst Guangdong, Acad Fdn Educ, Foshan 528200, Peoples R China
[3] Sichuan Univ, Business Sch, Chengdu 610064, Peoples R China
来源：
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS | 2022年 / 24卷 / 07期
关键词：
Hesitant fuzzy set; Distance measure; Similarity measure; Image segmentation; SIMILARITY MEASURES; CORRELATION-COEFFICIENTS; INFORMATION MEASURES; AGGREGATION; OPERATORS;
D O I：
10.1007/s40815-022-01328-6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Hesitant fuzzy set (HFS) is an important tool to describe uncertainty, and many scholars have proposed some different distance measures which are applied in decision-making. In this paper, based on the feature vector introduced by Zeng et al. (in: 2019 15th International Conference on Computational Intelligence and Security (CIS), 2019), we propose the distance measure of hesitant fuzzy elements (sets), investigate its related properties, develop some novel similarity measures of HFSs, and do comparison analysis with the existing similarity measures of HFSs. Finally, we apply them in image segmentation to illustrate that our distance measures and similarity measures are effective.
引用
收藏
页码：3134 / 3143
页数：10
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