在Fermatean模糊的双极软框架下的多属性决策
Ghous Ali1, Masfa Nasrullah Ansari1
1Division of Science and Technology, Department of Mathematics, University of Education, Lahore, Pakistan.
概括
费尔马特的模糊集合理论提供了一种管理不确定性的新方法. 这项研究引入了费尔马特模糊双极软集模型,增强了复杂场景中的决策.
科学领域:
- 数学 数学 是一个数学.
- 计算机科学 计算机科学
- 决策科学 决策科学 决策科学
背景情况:
- 费尔马特模糊集合为处理不确定性提供了一个强大的框架,优于直觉主义和毕达哥拉斯模糊集合.
- 现有的模糊集模型在捕捉不确定性下的真实世界决策细微差别方面存在局限性.
研究的目的:
- 介绍和研究新的费尔马特模糊双极软集 (FFBSS) 模型.
- 扩展现有的模糊双极软集和毕达哥拉斯模糊双极软集模型.
- 探索FFBSS模型在多属性决策 (MADM) 中的适用性.
主要方法:
- 开发了FFBSS模型的基本属性,包括子集,平等和运算 (交叉,联盟,AND,OR).
- 拟议的基本操作,如FFBSS.的Fermatean模糊加权平均值和得分函数.
- 使用了一种新的算法来支持MADM问题的 FFBSS 方法.
主要成果:
- 研究和定义FFBSS模型的关键属性和操作,并提供数值示例.
- 通过两个不同的MADM应用程序证明了FFBSS模型的有效性.
- 提供了比较分析,突出了FFBSS与现有模型的优势.
结论:
- FFBSS模型提供了一种更灵活,更可靠的方法来处理决策中的不确定性.
- 拟议的模型及其相关操作对于各种多属性决策问题是有效的.
- 在复杂的现实应用中,FFBSS代表了模糊集合理论的重大进步.
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