分析结核病的风险因素使用2型区间值的梯形模糊数字与爱因斯坦聚合运算符扩展到MCDM
1Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, 600127, India.
Heliyon
|September 9, 2024
概括
本研究介绍了重权聚合的Type-2间隔值模糊集 (T2IVFS),通过结合术语常数来增强决策. 新运营商有效地解决了复杂的多标准决策问题,例如选择结核病风险因素.
科学领域:
- 模糊的集合理论 模糊的集合理论
- 决策科学 决策科学
- 计算智能是一种计算智能.
背景情况:
- 区间值模糊集 (IVFS) 为不确定性提供了一个框架,但可能无法捕捉所有细微差别.
- 现有的聚合函数缺乏在操作过程中结合项的常数的能力.
- 2型模糊集合为模拟不确定性提供了更高水平的抽象.
研究的目的:
- 将区间值模糊集扩展到2型区间值模糊集 (T2IVFS).
- 开发使用爱因斯坦运算符用于T2IVFS的新型加权聚合函数.
- 为了引入类型-2间隔值模糊的爱因斯坦加权算术 (T2IVFEWA) 和几何 (T2IVFEWG) 聚合运算符.
主要方法:
- 通过扩展IVFS开发T2IVFS.
- 包含爱因斯坦运算符的加权聚合函数的制定.
- T2IVFEWA和T2IVFEWG运营商的组成及其特征分析.
- 结核病风险因素选择问题在混合多标准决策 (MCDM) 中的应用.
主要成果:
- 拟议的T2IVFS和相关的爱因斯坦加权聚合运算符得到了有效的定义.
- 开发的运营商在处理不确定性和术语常数方面表现出更强大的能力.
- 结核病风险因素选择的应用通过敏感性分析表明了拟议方法的实际实用性和稳定性.
结论:
- 以爱因斯坦加权聚合为T2IVFS的扩展为决策提供了更强大的工具.
- 拟议的运营商有效地解决复杂的MCDM问题,优于现有方法.
- 该方法为分析和选择不确定的环境中的最佳解决方案提供了一个强大的框架.
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