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Similarity measures of Pythagorean fuzzy sets based on combination of cosine similarity measure and Euclidean distance measure

机译:基于余弦相似度测量和欧几里德距离测量的毕达哥拉斯模糊集的相似性测量

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Similarity measures based-distance for intuitionistic fuzzy sets (IFSs) have been proposed to the literature. However, this sort of similarity measure has an impediment as it cannot fulfill the axiomatic definition of the similarity by providing the counter-intuitive cases. Due to the disadvantage, a similarity based-distance for Pythagorean fuzzy sets (PFSs) is proposed for this study. A combination of cosine similarity measures and Euclidean distance of PFSs is proposed. The PFS is the expansion of the IFSs and recently developed to manage the situation that cannot be depicted by IFS. PFS are characterized by the three degree such that membership degree, non-membership degree and hesitancy degree that satisfies the condition that square sum of its membership degree and non-membership degree is equal to or less than 1. A set of numerical examples are displayed to demonstrate the proposed similarity measure. Our approach do not give any counter-intuitive cases. It appears that our proposed similarity measure outperforms the similarity measure of IFSs especially in giving no counter-intuitive cases.
机译:对于直觉模糊集(IFSS)的相似度,已经提出了文献的距离。然而,这种相似度测量具有障碍,因为它不能通过提供反向直观的情况来满足相似性的公理定义。由于缺点,提出了为本研究提出了毕达哥兰模糊集(PFSS)的相似性。提出了余弦相似度测量和PFSS的欧几里德距离的组合。 PFS是IFSS的扩展,最近开发用于管理IFS无法描绘的情况。 PFS的特点是三个程度,使得满足其成员度和非隶属度等于或小于1的方案总和的条件的隶属度,非员额和犹豫学位等于或少于1.显示一组数值示例展示所提出的相似度措施。我们的方法不会给予任何反向直观的案例。似乎我们所提出的相似度测量占据IFSS的相似度测量,尤其是在不提供反向直观的情况下。

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