区间值图片模糊的决策框架与分区麦克劳林对称平均积累运算符
Muhammad Azeem1, Jawad Ali2, Jawad Ali3
1Department of Mathematics and Statistics, University of Agriculture Faisalabad, Punjab, 38000, Pakistan.
Scientific reports
|October 4, 2024
概括
本研究引入了新的间隔值图片模糊 (IVPF) 分区麦克劳林对称平均运算符,用于决策. 这些运营商有效地处理不确定性,并改善多标准决策过程.
科学领域:
- 决策科学 决策科学
- 模糊的集合理论 模糊的集合理论
- 信息融合 信息融合
背景情况:
- 间隔值图片模糊 (IVPF) 集扩展图片模糊集以建模复杂的不确定性.
- 现有的方法缺乏对IVPFS和标准分区之间的相互关系的可靠运算符.
研究的目的:
- 探索多个IVPFS和标准分区之间的相互关系.
- 为了引入新的IVPF分区麦克劳林对称平均运算符.
- 利用这些运营商开发一个多标准决策 (MCDM) 程序.
主要方法:
- 调查IVPF分区麦克劳林对称平均值和加权IVPF分区麦克劳林对称平均值运算符.
- 确定这些运营商的特殊情况.
- 开发和应用一个MCDM程序.
主要成果:
- 拟议的运营商表现出处理不确定性所需的特性.
- 开发的MCDM程序是实用的和有效的,如数字示例所示.
- 这种新方法证明了其在现有方法上的优越性.
结论:
- 新的IVPF分区运算符为在不确定性下做出决策提供了一个强大的工具.
- 拟议的MCDM方法增强了复杂决策问题的分析.
- 这项研究有助于在决策科学中推进模糊集合论的应用.
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