一个具有云模型,Z数字和间隔值的语言中性学集合的决策模型
Huakun Chen1,2, Jingping Shi1,2, Yongxi Lyu1,2
1School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.
Entropy (Basel, Switzerland)
|November 27, 2024
概括
这项研究引入了一个新的Z-间隔值的语言中性学集合-形-形云 (Z-IVLNS-TTC) 模型,以更好地处理不确定性. 这种新的方法改善了信息量化和复杂情景中的决策.
科学领域:
- 决策科学 决策科学
- 信息科学 信息科学 信息科学
- 人工智能的人工智能
背景情况:
- 间隔值的语言中性学集合 (IVLNSs),Z数和梯形云是模拟不确定性的关键.
- 现有的方法在准确量化和处理复杂的不确定的信息方面面临挑战.
研究的目的:
- 开发一种新的Z-间隔值的语言中性学集合-形-形云 (Z-IVLNS-TTC) 模型.
- 整合IVLNS和Z数以增强不确定性的表达.
- 尽量减少信息丢失和量化中的扭曲.
主要方法:
- 引入了一种IVLNS和Z数字的新组合.
- 建议采用Z-IVLNS-TTC模型来改进信息表示.
- 目标权重是使用多目标规划 (MOP) 计算的.
- 为Z-IVLNS-TTCs开发了一个基于p-norm的距离测量,灵感来自TOPSIS.
主要成果:
- 拟议的Z-IVLNS-TTC模型有效地减少了信息丢失和扭曲.
- 介绍了一种使用MOP的新客观权重计算方法.
- 一种新的距离测量方法可以提高不确定的信息的比较.
- 该方法在集团决策中证明了其实际适用性.
结论:
- Z-IVLNS-TTC模型为处理复杂的不确定性提供了一个强大的框架.
- 开发的方法为在不确定性下做出决策提供了有效的工具.
- 灵敏度分析和比较证实了该方法的有效性和可行性.
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