使用多个标准的决策和它们在现实生活中的应用之间,一般化二奥芬丁模糊集之间的不同距离
Murugan Palanikumar1, Nasreen Kausar2, Dragan Pamucar3,4,5
1Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India.
Scientific reports
|August 29, 2024
概括
这项研究引入了一般化的二奥芬丁模糊集合,增强了现有的模糊集合理论. 这些新套件提供了改进的应用程序,并克服了决策过程中的局限性.
科学领域:
- 模糊的集合理论 模糊的集合理论
- 决策 决策 决策 决策
- 多重标准决策分析分析
背景情况:
- 现有的模糊集合理论,如直觉,毕达哥拉斯和狄奥芬蒂斯模糊集合,在处理成员和非成员等级方面存在局限性.
- 需要更灵活和适用的模糊集模型来解决现实世界的复杂性.
研究的目的:
- 引入和定义通用的迪奥芬丁模糊集合,作为现有的模糊集合概念的新扩展.
- 探索与这些新集合相关的基本属性,关系和距离.
- 为了证明一般化迪奥芬丁模糊集的优越性和实际适用性,与现有的方法相比.
主要方法:
- 一般化狄奥芬丁模糊集合的定义及其基本属性.
- 新运营商的引入:必要性,可能性,准确性和评分功能.
- 开发新的距离测量方法,包括增强的规范化的欧几里德和汉明距离.
- 图像和反图像函数的定义用于通用的迪奥芬丁模糊关系.
- 应用基于流程图的多标准决策方法.
主要成果:
- 定义了广义的迪奥芬廷模糊集合,包括迪奥芬廷和毕达哥拉斯模糊集合.
- 引入了新的运营商和距离测量,增强了分析能力.
- 拟议的方法在数值示例中显示了与现有技术相比更高的性能.
- 实际例子说明了在日常场景中增强距离的实用性.
结论:
- 一般化狄奥芬模糊集合通过结合参考参数,有效地克服了以前模糊集合理论的局限性.
- 开发的运营商和距离措施为决策提供了更强大的框架.
- 增强的模糊集模型在实际应用中表现出更广泛的适用性和更高的有效性,特别是在多标准决策中.
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