一种新的MCDM方法来评估学生的就业能力心理学,使用复杂的毕达哥拉斯犹不决的模糊的Sugeno Weber聚合
1School of Sport and Art, Shandong Sport University, Jinan, 250000, Shandong, China. hexiao1617@163.com.
Scientific reports
|July 22, 2025
概括
本研究引入了一种新的多标准决策 (MCDM) 系统,使用复杂的毕达哥拉斯犹模糊集 (CPyHFS) 来管理学生在就业能力 (MSPE) 的心理. 该研究确定职业指导研讨会是增强学生职业发展的最佳选择.
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
- 教育心理学教育心理学
背景情况:
- 在就业方面有效管理学生心理 (MSPE) 对于职业成功至关重要.
- 像复杂模糊犹集 (CFHS) 和复杂直觉模糊犹集 (CIFHS) 这样的现有框架在处理满意度和不满意度方面存在局限性.
- 在安排学生信息以有效解决MSPE问题方面存在重大挑战.
研究的目的:
- 提出一种基于复杂的毕达哥拉斯犹不决的模糊集 (CPyHFS) 的新型多标准决策 (MCDM) 系统,用于管理MSPE.
- 引入新的聚合运算符:复杂的毕达哥拉斯犹模糊的Sugeno Weber加权平均 (CPyHFSWWA) 和复杂的毕达哥拉斯犹模糊的Sugeno Weber加权几何 (CPyHFSWWG).
- 建立使用CPyHFS的MCDM算法,用于选择MSPE中最佳的替代方案.
主要方法:
- 基于Sugeno Weber t-norm和t-conorm的新型聚合运营商 (CPyHFSWWA和CPyHFSWWG) 的开发.
- 使用复杂的毕达哥拉斯犹不决的模糊集合 (CPyHFS) 制定一个MCDM算法.
- 提出的方法应用于一个案例研究,涉及10个替代方案和MSPE的四个标准.
主要成果:
- 提出的MCDM方法有效地选择了管理学生在就业能力方面的最佳选择.
- 在案例研究中",职业指导研讨会"被确定为最合适的替代方案.
- 与现有运营商相比,已建立的方法证明了可靠性,灵活性和适用性.
结论:
- 基于复杂的毕达哥拉斯犹模糊集 (CPyHFS) 的MCDM系统为MSPE挑战提供了强大的解决方案.
- 新开发的聚合运营商增强了复杂场景中模糊决策的能力.
- 这些发现为教育机构和政策制定者提供了有价值的工具,旨在提高学生的就业能力.
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