关于多维模糊集合的距离,相似性和度的测量
Jomal Josen1, Sunil Jacob John2, Jobish Vallikavungal3,4
1Department of Mathematics, St. Thomas College Palai (Autonomous), Arunapuram P.O., Kottayam, Kerala, 686 574, India.
Scientific reports
|January 10, 2026
概括
这项研究为多维模糊集合引入了新的距离和相似度指标,增强了决策能力. 拟议的Sigma措施在复杂的聚合任务中提供了更好的性能.
科学领域:
- 模糊的数学 模糊的数学
- 决策科学 决策科学
- 信息理论 信息理论
背景情况:
- 多维模糊集对于复杂的决策和数据聚合至关重要.
- 现有的距离和相似度措施可能无法充分捕捉多维模糊空间中的关系.
- 了解距离,相似性和之间的相互作用对于先进的模糊集合论至关重要.
研究的目的:
- 定义多维距离测量的公理.
- 在模糊空间中开发规范的距离和相似度.
- 引入补充不变的近距离测量方法,并探索它们与多维的联系.
主要方法:
- 多维距离测量的公理定义.
- 制定一个标准化距离和相似性测量的框架.
- 介绍了西格玛距离,西格玛相似度和西格玛度的测量方法.
- 使用拟议的措施分析决策问题.
主要成果:
- 在多维模糊集合中规范距离和相似性的新框架.
- 引入补充不变的近距离测量措施.
- 建立了距离,相似性和多维之间的关系.
- 在决策场景中证明了拟议的西格玛措施的优势.
结论:
- 拟议的西格玛距离,西格玛相似性和西格玛测量方法为分析模糊集合及其补充提供了一个平衡的方法.
- 开发的框架为多维模糊环境中的决策和聚合提供了一个强大的工具.
- 对比分析证实了拟议模型在现有方法上的优越性.
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