在复杂的球形模糊知识中为Web 3.0授权去中心化身份系统
Masfa Nasrullah Ansari1, Abdul Razaq2, Hanan Alolaiyan3
1Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Scientific reports
|October 9, 2024
概括
本研究在复杂的球形模糊环境中引入了新的Yager聚合运算符,以改善Web 3.0分散身份管理的决策,增强数字隐私和安全.
科学领域:
- 计算机科学 计算机科学
- 信息安全 信息安全
- 人工智能的人工智能
背景情况:
- 网络3.0强调去中心化,安全性和个性化的用户体验.
- 分散身份管理 (DIM) 对于在Web 3.0中管理数字人物至关重要.
- 多标准决策 (MCDM) 的挑战需要对不准确的数据进行强大的聚合技术.
研究的目的:
- 在复杂球形模糊 (CSF) 环境中使用Yager聚合运算符来增强Web 3.0决策场景.
- 为了引入新的聚合运算符,复杂的球体模糊的Yager-Ordered加权平均 (CSFYOWA) 和复杂的球体模糊的Yager-Ordered加权几何 (CSFYOWG).
- 为MCDM问题开发算法,并将其应用于优化Web 3.0.0中的数字身份和数据隐私.
主要方法:
- 开发两个新的聚合运营商:CSFYOWA和CSFYOWG.
- 为CSF框架阐明结构特征和更新的评分功能.
- 建议运算符和算法的应用,以解决Web 3.0隐私保护中的MCDM问题.
主要成果:
- 引入新的CSFYOWA和CSFYOWG运营商,为CSF提供了改进的评分功能.
- 为Web 3.0隐私挑战量身定制的有效MCDM算法的开发.
- 通过比较分析来证明拟议技术的有效性.
结论:
- 拟议的Yager聚合运算符和MCDM算法为Web 3.0环境中的决策提供了显著的进步.
- 这些方法有效地解决了不确定性,并增强了数字身份和数据的隐私解决方案.
- 这项研究证实了新技术在Web 3.0应用程序的现有方法上的优越性.
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