评估具有嵌入式辅助层间相似性的多重网络的稳定性和可缩小性
Haoran Nan1, Senquan Wang1, Chun Ouyang1
1Beijing University of Chemical Technology, College of Information Science and Technology, Beijing, China.
Physical review. E
|June 19, 2025
概括
我们开发了嵌入辅助层间相似性 (EATSim),以更好地测量网络层之间的关系. 通过考虑内部结构和层之间的连接,EATSim提高了对复杂系统的理解.
科学领域:
- 复杂系统科学 复杂系统科学
- 网络科学 网络科学
- 数据科学数据科学数据科学
背景情况:
- 了解多重网络对于分析交通和社交网络等相互连接的系统至关重要.
- 目前用于测量层间相似性的方法通常只捕获部分信息,限制了全面的分析.
- 变化的跨层传播是复杂系统动态的一个关键方面.
研究的目的:
- 提出一种新的方法,即嵌入辅助层间相似性 (EATSim),用于准确地测量多重网络中的层间相似性.
- 提供一个更全面的框架,整合层内部结构相似性和跨层节点对齐.
- 提高复杂的相互连接系统的分析和理解.
主要方法:
- 开发了EATSim,它结合了内部层结构相似性和跨层结对齐一致性.
- 嵌入式网络嵌入技术,以捕获底层的几何性质.
- 在合成和现实世界的多重网络上进行了广泛的实验.
主要成果:
- EATSim有效地捕捉了相互连接的网络层之间的几何相似性.
- 与现有方法相比,在层间相似性测量准确度方面取得了显著的改进.
- 在预测网络稳定性和网络可缩小性方面实现了最先进的性能.
结论:
- EATSim提供了一种更全面,更准确的方法来量化多重网络中的层间相似性.
- 该方法增强了理解和管理复杂系统的能力.
- EATSim显示了网络分析,稳定性评估和系统优化应用的巨大潜力.
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