一些复杂的概率犹不决的模糊聚合运算符及其用于多属性决策的应用.
Yanpo Yang1, Baoquan Ning2, Fengjuan Tian1
1School of Mathematics and Statistics, Liupanshui Normal University, Liupanshui, 553004, China.
Scientific reports
|February 5, 2025
概括
本研究介绍了复杂的概率犹模糊集合 (CPHFS),用于处理决策中的随机性和模糊性. 它开发了新的聚合运算符和复杂数据的多属性决策 (MADM) 过程.
科学领域:
- 模糊的数学 模糊的数学
- 决策科学 决策科学 决策科学
- 信息理论 信息理论
背景情况:
- 复杂模糊集 (CFS) 和概率犹模糊集 (PHFS) 处理特定类型的不确定性.
- 现有的模型可能无法充分捕捉现实数据中的同时随机性和模糊性.
- 需要先进的模糊集合理论来解决复杂的决策场景.
研究的目的:
- 提出一个新的模糊集,复杂的概率犹模糊集 (CPHFS),集成CFS和PHFS概念.
- 为CPHFS开发基本操作和聚合操作员.
- 使用CPHFS建立一个多属性决策 (MADM) 框架.
主要方法:
- 复杂的概率犹不决的模糊元素 (CPHFE) 的定义及其基本操作.
- 聚合运营商的发展:CPHFWA,CPHFWG,CPHFHM,CPHFGHM,以及它们的加权形式.
- 在CPHF环境中构建一个逐步的MADM流程.
主要成果:
- 建立了CPHFE的基本操作和操作法律.
- 引入了新的聚合运算符,以解释属性相互关系.
- 通过实践示例 (购买汽车) 证明了拟议的MADM流程的有效性.
结论:
- CPHFS有效地模拟复杂的决策信息,同时具有随机性和模糊性.
- 拟议的MADM方法与交互性属性的现有方法相比,提供了更高的性能.
- 该框架为解决复杂的多属性决策问题提供了一个强大的工具.
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