preprintDagstuhl Research Online Publication ServerJan 1, 2025GREEN OA

Identifying Resilient Communities in Road Networks: A Path-Based Embedding Approach

WCWagner, ChristopherDSDodge, SomayehADAlizadeh, Danial

University of California, Santa Barbara

Indexed indatacite

Abstract

Effective resilience analysis of road networks is fundamental to building sustainable and disaster prepared cities. Identifying which road segments share similar vulnerabilities is important for pinpointing high-risk areas within the network and implementing measures to safeguard them against future disruptions. Graph-based community detection can be applied to group together areas of the network sharing similar structural vulnerabilities. However, current graph-based community detection methods either struggle with integrating node features during partitioning or do not account for the path-based dependencies in road networks. This paper introduces the Path-based Community Embedding (PCE) model, an approach…

Citation impact

1,600
total citations
FWCI
311.75
Percentile
100%
References
0
Citations per year

Authors

3
  • WC
    Wagner, ChristopherCorresponding

    University of California, Santa Barbara

  • DS
    Dodge, Somayeh

    University of California, Santa Barbara

  • AD
    Alizadeh, Danial

    University of California, Santa Barbara

Topics & keywords

Keywords
  • Autoencoder
  • Computer science
  • Encoder
  • Graph
  • Latent variable
  • Benchmark (surveying)
  • Artificial intelligence
  • Feature learning
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