一种新的多属性组决策方法,基于间隔值的费尔马特犹不决的模糊环境下的爱因斯坦邦费罗尼运算符
Siyue Lei1, Xiuqin Ma1,2, Hongwu Qin3,4
1College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, Gansu, China.
Scientific reports
|May 29, 2024
概括
本研究引入了使用区间值的费尔马特犹不决的模糊集 (IVFHFS) 进行多属性组决策 (MAGDM) 的新方法. 这种新的方法增强了数据不确定性处理和属性关系考虑,以获得更好的决策结果.
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
- 人工智能的人工智能
背景情况:
- 区间值的费尔马特犹模糊集 (IVFHFSs) 提供了对不确定的决策信息的高级处理.
- 现有的多属性组决策 (MAGDM) 方法缺乏全面的操作规则和灵活性,并且不考虑属性相互依赖.
研究的目的:
- 提出一种新的MAGDM方法,利用区间值的费尔马特犹不决的模糊集合 (IVFHFSs) 和爱因斯坦的邦费罗尼运算符.
- 在IVFHFSs中扩大对爱因斯坦t-norms运行定律的理解.
- 开发灵活的聚合运算符,以考虑属性关系.
主要方法:
- 在IVFHFSs下对爱因斯坦t-norms的运行定律进行了彻底的检查.
- 介绍区间值的费尔马特犹不决的模糊的爱因斯坦邦费罗尼平均值和加权的邦费罗尼平均值运算符.
- 开发一种新的MAGDM方法,包括这些运营商.
主要成果:
- 在IVFHFS中为爱因斯坦t-norms建立了全面的操作规律.
- 引入了新的爱因斯坦邦费罗尼聚合运算符,提供了增强的灵活性和属性相互依赖性的考虑.
- 通过心血管疾病诊断应用证明了拟议方法的有效性.
结论:
- 拟议的MAGDM方法通过结合先进的模糊集合理论和聚合技术,有效地解决了现有方法的局限性.
- 开发的爱因斯坦·邦费罗尼运算符为不确定性下决策提供了更强大的框架.
- 在心血管疾病诊断中的应用验证了新方法的实际实用性和准确性.
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