Scholarlink

<p>The distance measure is a great resource to analyse the disparity of Fermatean fuzzy set (FFSs), which significantly deals the ambiguity. Although prior research offered plenty of distance measurements for FFSs, most of those fail to satisfy the distance constraints or build contradictions. Therefore, in this investigation, we offer a unique distance measure made up of an aspect of FFS. In the context of consistency among the two FFSs, the new distance measure is formulated using the fundamental function that comprises the membership, non-membership, and hesitation grades. It indicates that the recommended measure possesses the features of the formal meaning of the distance measure. A comparison with prior measures of distance to the presented distance measure reveals that the offered measure of distance does not yield any adverse events. Moreover, research investigations on multi-criteria decision-making (MCDM), image fusion and image segmentation challenges confirm the suggested distance measure’s practical usefulness.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A design and development of distance measure for Fermatean fuzzy sets with varied applications in real-time

  • 期刊论文

  • 发表日期：

    2025年4月23日

查看全文
  • R. Premalatha,
  • K. Somasundaram

摘要

The distance measure is a great resource to analyse the disparity of Fermatean fuzzy set (FFSs), which significantly deals the ambiguity. Although prior research offered plenty of distance measurements for FFSs, most of those fail to satisfy the distance constraints or build contradictions. Therefore, in this investigation, we offer a unique distance measure made up of an aspect of FFS. In the context of consistency among the two FFSs, the new distance measure is formulated using the fundamental function that comprises the membership, non-membership, and hesitation grades. It indicates that the recommended measure possesses the features of the formal meaning of the distance measure. A comparison with prior measures of distance to the presented distance measure reveals that the offered measure of distance does not yield any adverse events. Moreover, research investigations on multi-criteria decision-making (MCDM), image fusion and image segmentation challenges confirm the suggested distance measure’s practical usefulness.