Hybrid modelling of particulate systems and compaction processes

颗粒系统和压实过程的混合建模

• 批准号: 2436507
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2436507
• 关键词: Hybrid; modelling; particulate; systems; compaction

Graphs and networks play an important role in modeling and analyzing complex interconnected systems such as transportation networks, integrated circuits, power grids, citation graphs, and biological and artificial neural networks. Graph clustering algorithms can be used to detect groups of strongly connected vertices and identify communities within networks, with spectral clustering in particular being a well-known and powerful technique. This project aims to develop novel extensions to traditional spectral clustering algorithms to enable community detection in both directed and time-evolving graphs.

图和网络在建模和分析复杂的互连系统（例如交通网络、集成电路、电网、引文图以及生物和人工神经网络）方面发挥着重要作用。图聚类算法可用于检测强连接的顶点组并识别网络内的社区，特别是谱聚类是一种众所周知且强大的技术。该项目旨在开发传统谱聚类算法的新颖扩展，以实现有向图和时间演化图中的社区检测。