Intuitionistic Fuzzy Modulus Similarity Measure

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Pawan Gora
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引用次数: 0

Abstract

The concept of intuitionistic fuzzy sets (IFSs) is an expected explanation for finding the appropriate information. It originated from concept of fuzzy set (FS) theory, which extends the classical conception of a fuzzy set. This paper examines a number of widely employed similarity measures then proposes an IFSs modulus similarity measure and a weight similarity measure. Initially, the authors have discussed numerous existing similarity measures, some of which are unable to justify the axioms of being a similarity measure. Furthermore, some numerical examples are presented to compare the existing similarity measures with the proposed similarity measure. The proposed similarity measure is a practical and effective method for determining the qualitative similarity between IFSs, which do not have any paradoxical nature. In addition, the proposed similarity measure has been demonstrated practically in pattern recognition and medical diagnosis problem. Suggestions for future research comprise the conclusions of the paper.
直觉模糊模相似测度
直觉模糊集(ifs)的概念是寻找适当信息的预期解释。它起源于模糊集理论的概念,是对经典模糊集概念的扩展。本文考察了一些广泛使用的相似性度量,然后提出了ifs模数相似性度量和权重相似性度量。最初,作者讨论了许多现有的相似性度量,其中一些无法证明作为相似性度量的公理。最后,给出了一些数值算例,将现有的相似测度与所提出的相似测度进行了比较。所提出的相似性度量是确定ifs之间的定性相似性的实用而有效的方法,ifs不具有任何悖论性质。此外,所提出的相似度度量在模式识别和医学诊断问题中得到了实践验证。本文的结论是对未来研究的建议。
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来源期刊
International Journal of Decision Support System Technology
International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
18.20%
发文量
40
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