Advancing Urban Seismic Resilience via Complex Networks: Theory, Modeling, Technical Practices and Future Perspectives

Urban seismic resilience represents a central concern in disaster risk management, reflecting the profoundly destructive nature of earthquakes. Conventional engineering-based assessment methods are often inadequate to meet the demands of risk response in densely interconnected urban systems. In this context, complex network theory offers a valuable analytical framework, as it can reveal the interdependencies among system components and the mechanisms of cascading failure, thereby providing reliable support for risk management. Following the PRISMA guidelines, this study systematically reviews the literature published up to June 2026 and synthesizes core concepts, modeling approaches, assessment techniques, and practical applications. The field is evolving from early linear indicators toward coupled network modeling across urban systems and dynamic resilience simulation, a development enabled by artificial intelligence and digital twin technologies. Nevertheless, considerable challenges remain. The limited coupling between social and physical systems constrains quantitative assessment, while data fragmentation and oversimplified models undermine the reliability of the resulting evaluations. This study underscores the systematic role of complex network theory and identifies key directions for future research on the seismic resilience of urban systems. As technological capabilities advance, the integration of system coupling mechanisms, digital twin benchmarks, and AI-assisted decision support is expected to facilitate the development of implementable, next-generation tools suited to the era of artificial intelligence.