Scholarlink

<p>This paper introduces a novel numerical characteristic of hesitant fuzzy soft sets called their scored-energy. We introduce this concept as a combination of two very different tools, namely, scores of hesitant fuzzy elements and singular values of a (not- necessarily square) matrix. The latter idea replicates the concept of energy or nuclear norm of a matrix, which has excellent analytical abilities in graph theory and applications in fields such as statistics or signal processing. Natural algorithms establish applications of scored-energies to both clustering and decision-making. Through examples, we demonstrate how these new techniques are efficient and implementable in practice. Comparisons are conducted that prove their validity, reliability, and credibility.</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

Decision-Making and Clustering Algorithms Based on the Scored-Energy of Hesitant Fuzzy Soft Sets

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月19日

查看全文
  • José Carlos R. Alcantud,
  • Nenad Stojanović,
  • Ljubica Djurović,
  • Maja Laković

摘要

This paper introduces a novel numerical characteristic of hesitant fuzzy soft sets called their scored-energy. We introduce this concept as a combination of two very different tools, namely, scores of hesitant fuzzy elements and singular values of a (not- necessarily square) matrix. The latter idea replicates the concept of energy or nuclear norm of a matrix, which has excellent analytical abilities in graph theory and applications in fields such as statistics or signal processing. Natural algorithms establish applications of scored-energies to both clustering and decision-making. Through examples, we demonstrate how these new techniques are efficient and implementable in practice. Comparisons are conducted that prove their validity, reliability, and credibility.