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通过基于CODAS方法和q-ROPFS聚合运营商的股票投资分配运营资金

Sumbal Ali¹, Ikram Ullah², Salma Khan¹

¹Department of Mathematics and Statistics, Hazara University, Mansehra, Khyber Pakhtunkhwa 21300, Pakistan.

|October 27, 2025

概括

本研究为q-rung orthopair图片模糊软模型引入了新的几何聚合运算符,增强了复杂环境中的决策. 新兴运营商在使用CODAS方法进行股票投资选择方面表现出色.

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
计算智能是一种计算智能.

背景情况:

在决策过程中,管理不确定性至关重要.
现有的模糊模型在处理复杂的不确定性方面存在局限性.
这种Q-rung orthopair图片模糊软模型为不确定性管理提供了一个强大的框架.

研究的目的:

引入新的几何聚合运算符 (q - ROPF S t WG 和 q - ROPF S t OWG) 在 qrung- orthopair 图像模糊的软环境中.
确定这些新运算符的理论特性.
解决聚合运营商在动态现实场景中的实际应用方面的差距.

主要方法:

开发了新的几何聚合运算符:q - ROPF S t WG 和q - ROPF S t OWG. 这两种运算符的运算方法是:
使用复杂决策分析 (CODAS) 方法,在多属性决策 (MADM) 框架内应用这些运算符.
通过现实世界股票投资选择问题进行验证,包括参数分析和比较评估.

主要成果:

拟议的ROPF运营商表现出强性和适应性,这些运营商具有强性和适应性.
与现有的决策方法相比,综合方法显示出优越性和更大的灵活性.
在实际股票投资选择场景中的有效应用证实了该模型的实用性.

结论:

新型的几何聚合运算符增强了q-rung orthopair图片模糊软模型的功能.
提出的方法为复杂的决策问题提供了可靠和灵活的工具.
这项研究促进了聚合运算符在动态和不确定的环境中的实际应用.

关键词:

聚合运营商是一个聚合运营商.通过CODAS的方法.决策决策是做出决定的.优化优化优化优化 q-rung整形夫妇图片模糊的软数字

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