Distance Measure of Hesitant Fuzzy Sets and its Application in Image Segmentation
Distance Measure of Hesitant Fuzzy Sets and its Application in Image Segmentation
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DOI：
10.1007/s40815-022-01328-6
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发表时间：
2022-06
影响因子：
4.3
通讯作者：
Wenyi Zeng;Rong Ma;Deqing Li;Qian Yin;Zeshui Xu
中科院分区：
文献类型：
--
作者：
Wenyi Zeng;Rong Ma;Deqing Li;Qian Yin;Zeshui Xu
犹豫模糊集（HFS）是描述不确定性的重要工具，许多学者提出了不同的距离测度，并将其应用于决策中。本文基于Zeng等（in：2019 15th International Conference on Computational Intelligence and Security（CIS），2019）提出的特征向量，提出了犹豫模糊元素（集）的距离度量，研究了其相关性质，提出了一些新的HFSs相似性度量，并与已有的HFSs相似性度量进行了比较分析。最后，我们将它们应用于图像分割，以说明我们的距离度量和相似性度量是有效的。
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.