arXiv (OAI Expanded)
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Data-Driven Stress Testing of Intermodal Freight Networks Using GAN-Generated Disruption Scenarios
Intermodal freight networks are increasingly exposed to correlated, multi-mode disruptions, yet resilience assessments often rely on historical or uncorrelated scenarios that understate systemic risk. This paper develops a data-driven stress-testing framework integrating generative adversarial netwo
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