汽车工业具有先进的决策支持系统和Aczél-Alsina Hammy平均运营商的关键影响
Abrar Hussain1,2,3, Kifayat Ullah1,4, Zeeshan Ali5
1Department of Mathematics, Riphah International University (Lahore Campus), Lahore, 54000, Pakistan.
Scientific reports
|January 7, 2026
概括
本研究引入了使用球形模糊集的新数学模型,以改善汽车行业的决策. 这些模型增强了涉及模糊的人类信息的复杂选择的分析,以获得更好的结果.
科学领域:
- 决策科学 决策科学
- 模糊的数学 模糊的数学
- 汽车工程 汽车工程
背景情况:
- 汽车行业在经济发展,创新和可持续移动方面发挥的关键作用.
- 需要结构化的决策分析系统来处理复杂的选择和汽车环境中模糊的人类信息.
- 现有框架在有效管理专家判断中的不确定性和模糊性的局限性.
研究的目的:
- 开发新的数学运算符用于汽车行业的决策分析,使用球形模糊集.
- 改善处理多属性组决策 (MAGDM) 问题中的不确定性和模糊性.
- 为了引入球形模糊的Aczel Alsina Hamy平均值 (SFAHM),SFAWHM,SFADHM和SFAWDHM运算符.
主要方法:
- 探索球形模糊集 (SFSs) 来表示模糊的人类判断.
- 修改和整合哈米平均值 (HM) 模型与Aczel Alsina操作.
- 开发新的SFAHM,SFAWHM,SFADHM和SFAWDHM运营商,并调查它们的特性.
- 为MAGDM问题制定智能决策算法.
主要成果:
- 拟议的SFAHM和SFAWHM运营商,以及它们的DHM概括 (SFADHM,SFAWDHM),有效地处理决策中的不确定性.
- 一个数值示例展示了在汽车工业中选择最佳替代品时开发的运营商的应用和有效性.
- 对比分析证实了拟议的数学模型在现有方法论上的优越性和验证性.
结论:
- 新开发的球形模糊运算符为汽车行业的复杂决策提供了强大的框架.
- 拟议的MAGDM算法提供了一种可靠的方法,用于在不确定性下提供专家意见的集团决策.
- 该研究验证了球形模糊集与Aczel Alsina Hamy平均运算相结合的增强能力,用于现实世界的应用.
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