.png){kind=icon}
返回
Temporal network analysis using zigzag persistence
.png){kind=icon}
OA
AI
DOI：10.1140/epjds/s13688-023-00379-5.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work presents a framework for studying temporal networks using zigzag persistence, a tool from the field of Topological Data Analysis (TDA). The resulting approach is general and applicable to a wide variety of time-varying graphs. For example, these graphs may correspond to a system modeled as a network with edges whose weights are functions of time, or they may represent a time series of a complex dynamical system. We use simplicial complexes to represent snapshots of the temporal networks that can then be analyzed using zigzag persistence. We show two applications of our method to dynamic networks: an analysis of commuting trends on multiple temporal scales, e.g., daily and weekly, in the Great Britain transportation network, and the detection of periodic/chaotic transitions due to intermittency in dynamical systems represented by temporal ordinal partition networks. Our findings show that the resulting zero- and one-dimensional zigzag persistence diagrams can detect changes in the networks' shapes that are missed by traditional connectivity and centrality graph statistics.
Keyword:
Zigzag persistence
Temporal graph
Dynamical network
Topological data analysis
Persistent homology
Transportation network
期刊
IF:
2.5
论文数:
693
被引数:
1.6K
机构
引用论文
Challenges to pharmaceutical policymaking: lessons from Australia’s national medicines policy对药品政策制定提出的挑战：来自澳大利亚国家药物政策的经验教训OAAI
OAAI分享收藏Socio-material practices in classrooms that lead to the social participation or social isolation of disabled pupils课堂中导致残疾学生社会参与或社会孤立的社物质实践
OAAI
OAAI分享收藏Anatomical and ultrastructural adaptations of seagrass leaves: an evaluation of the southern Atlantic groups.png)
Protoplasma
ProtoplasmaIF0
PREAI
分享收藏分享收藏
查看更多内容