群组决策支持系统基于多粒度分数或三次模糊的2元组语言信息模型
Muhammad Qiyas1, Muhammad Naeem2, Neelam Khan3
1Department of Mathematics, Riphah International University, Faisalabad Campus, Pakistan.
Heliyon
|December 13, 2024
概括
本研究引入了一种新的决策支持模型,用于使用多粒度分数或三位数模糊的2元组语言 (FOF2TL) 信息进行复杂的群组决策. 该模型通过整合模糊集和语言方法来提高决策准确性,以获得更好的数据一致性和专家权重.
科学领域:
- 决策科学 决策科学
- 模糊逻辑系统 模糊逻辑系统
- 计算智能是一种计算智能.
背景情况:
- 多标准集团决策 (MCGDM) 提出了复杂,不确定的信息带来的挑战.
- 现有的模型与多粒度和模糊的语言数据作斗争.
- 需要强大的决策支持系统来处理异构信息.
研究的目的:
- 为MCGDM问题提出一个新的决策支持模型.
- 处理多粒度的分数或三位数模糊的2元组语言 (FOF2TL) 信息.
- 制定一个框架,使团队的决策一致和准确.
主要方法:
- 分数正三元模糊集合和二元组的语言方法的集成.
- 对多颗粒FOF2TL信息一致性的转换函数的定义.
- 运用阿基米德的copula和co-copula用于操作规律.
- 分数式或三位数模糊的2元组语言Banzhaf Choquet-Copula聚合 (FOF2TLBCCA) 运算符的开发.
- 确定专家和属性集模糊指标的方法.
主要成果:
- 引入了一种新的FOF2TL模型,增强数据处理能力.
- 定义了新的运营法律和聚合运营商 (FOF2TLBCCA).
- 建立了一个计算专家和属性重要性的方法.
- 拟议的模型在数字案例研究中证明了决策结果的改善.
结论:
- 开发的决策支持模型有效地解决了复杂的MCGDM问题与FOF2TL信息.
- 拟议的方法为提高集团决策准确性和可靠性提供了有价值的工具.
- FOF2TLBCCA 运营商提供了一种灵活而强大的方法来汇总不确定的语言信息.
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