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Graph neural network-based identification of vulnerable regions in spatial complex networks via virtual node model | Synapse
March 3, 2026
Graph neural network-based identification of vulnerable regions in spatial complex networks via virtual node model
DT
Dingrong Tan
XS
Xiaoda Shen
YD
Ye Deng
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Puntos clave
Identification of vulnerable regions enhances the resilience of spatial networks, enabling better monitoring.
A significant improvement of 25% in prediction accuracy was achieved through the virtual node model approach.
Employing graph neural networks reveals intricate relationships in spatial complex networks via network analysis.
Findings support the need for advanced tools in network management, particularly in monitoring critical infrastructures.
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Tan et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75cf1c6e9836116a26412
https://doi.org/https://doi.org/10.1016/j.ress.2026.112304