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基于CRITIC WASPAS的循环图片模糊信息的数字经济经济增长的决策算法

Junguang Gao¹, Ziyao Lin², Quan Liu³

¹Beijing Research Institute of Frontier Science, Beijing, 102488, China.

Scientific reports

|December 25, 2025

概括

循环图片模糊集有助于数字经济增长战略的选择. 电子治理和数字政策改革是经济增长的最佳策略,得到了CRITIC-WASPAS方法的验证.

科学领域:

决策科学决策科学
经济政策经济政策
信息系统信息系统信息系统

背景情况:

数字经济的增长需要在不确定性中选择有效的战略.
传统的决策模式在数字化转型中与复杂的多属性问题作斗争.
模糊集合论提供了一个强大的框架来处理固有的不确定性.

研究的目的:

开发和应用一种使用圆形图像模糊集 (CPFS) 的新型决策模型,用于评估数字经济增长战略.
在CPFS框架内整合CRITIC (通过相互关联的标准重要性) 和WASPAS (产品评估的加权总和) 方法.
在不确定的环境中为多属性集团决策 (MAGDM) 提供可靠的工具.

主要方法:

使用圆形图像模糊集 (CPFS) 来建模战略评估中的不确定性.
应用了CRITIC方法来确定基于相互依赖的客观属性权重.
采用WASPAS方法对战略替代品进行排名.
开发了一种MAGDM算法,将CPFS与CRITIC-WASPAS集成为数字经济增长的案例研究.

主要成果:

提出的基于CPFS的CRITIC-WASPAS模型有效评估了五个数字经济增长战略.
电子治理和数字政策改革被确定为最优的战略.
敏感性分析和比较评估证实了该模型的稳定性和可靠性.

结论:

综合CPFS,CRITIC和WASPAS方法为数字经济中的战略决策提供了一个强大的框架.
该模型增强了在选择经济增长战略时应对不确定性和复杂性的能力.
调查结果支持基于证据的政策制定,以促进数字经济的进步.

关键词:

这就是Critic-Waspas技术.圆形图片模糊的集合决策方式决策方式数字经济中的经济增长

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