具有犹值的新型复杂模糊距离测量及其在复杂决策问题中的应用
Madad Khan1, Safi Ullah2, Muhammad Zeeshan3
1Department of Mathematics, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
Scientific reports
|June 20, 2024
概括
这项研究引入了新的复杂模糊犹距离测量方法,以更好地量化复杂数据中的不确定性. 这些新措施通过结合犹来增强决策算法,改进现有的复杂模糊距离测量 (CFDM).
科学领域:
- 模糊的数学 模糊的数学
- 信息理论是信息理论.
- 决策科学科学 决策科学
背景情况:
- 复杂的模糊距离测量 (CFDM) 对高维数据至关重要,但往往忽略了数据的犹.
- 现有的CFDM很难表示复杂数据集固有的不确定性或不准确性的程度.
- 处理不确定性和不精确性在各种科学和工程领域至关重要.
研究的目的:
- 引入新的复杂模糊距离测量方法,特别是复杂模糊犹距离测量方法和复杂模糊欧几里德犹距离测量方法.
- 为了概括现有的复杂模糊的正常化哈明和欧几里德距离测量.
- 开发一个强大的决策算法,将这些新措施整合到复杂的现实世界问题中.
主要方法:
- 开发基于复杂的模糊集的新距离测量方法,其中包含一个犹度.
- 在拟议的CFDM框架内引入新的复杂模糊运算和初级结果.
- 制定一种新的决策算法,利用拟议的CFDM.
主要成果:
- 拟议的复杂模糊犹距离措施有效量化数据犹,这是以前CFDMs的一个局限性.
- 建立了新的复杂模糊运算和结果,扩大了理论基础.
- 开发的决策算法在处理复杂问题时表现出强大的应用.
结论:
- 新的复杂模糊犹距离测量方法在分析复杂和不确定的数据方面取得了重大进展.
- 拟议的措施和决策算法为现实世界决策问题提供了更全面的方法.
- 对比分析证实了拟议的CFDM在特定环境中优于现有方法的优势.
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