Complex system evolution of structural resilience, propagation dynamics and intelligent governance in Chinas railway network based on multi-layer coupled networks

Against the backdrop of China's high-speed rail (HSR) network achieving global leadership in scale (48,000km, 70% worldwide) yet facing structural fragility, disaster-chain coupling, and regional imbalance, this study constructs a "structural resilience-propagation dynamics-intelligent governance" trinity framework. By integrating multi-layer coupled network theory, this paper develop: (1).A spatiotemporal-weighted betweenness centrality algorithm dynamically identifying critical nodes using Beidou data; (2).A multi-layer SEIR model quantifying epidemic-economic dual diffusion with linear threshold mechanisms; (3).A reinforcement learning framework optimizing anti-siphoning policies. Key findings reveal: Wuhan hub fault recovery time reduced by 50% through backup topology, Beijing West Station achieved 89% epidemic blocking via dual-channel quarantine, and the Chengdu-Chongqing regional Gini coefficient decreased 29% via frequency regulation. The paradigm shift from static planning to real-time adaptive governance offers a "China solution" for global railway resilience, evidenced by magnetic levitation standards (e.g., 18% energy savings in Saudi NEOM line) and multi-disaster defense systems (35% faster ASEAN flood recovery).