A CAS driven framework integrating entropy cloud and fuzzy cognitive map enhances disaster resilience in urban old communities

The increasing risks from both natural and human-made disasters, exacerbated by the dense concentration of urban populations and assets, pose serious challenges for disaster prevention and response. These challenges are especially acute in urban old communities, which often lack sufficient resistance and adaptive capacity. This study focuses on urban old communities and, drawing on Complex Adaptive Systems (CAS) theory and the concept of community resilience, explores the resource systems that support resilience enhancement. A disaster resilience evaluation index system is developed, and the entropy-weight method combined with the cloud model is used to assess the current level of resilience. Key factors influencing resilience are identified, and a fuzzy cognitive map (FCM) model is applied to simulate their dynamic interactions and mechanisms of influence. The results indicate that low disaster resilience in urban old communities stems primarily from aging infrastructure, weak ecological systems, imbalanced population structures, economic instability, insufficient organizational capacity, and limited cultural awareness. Among these, the resilience of infrastructure and cultural awareness emerge as the most critical factors, representing key pathways for resilience enhancement. Based on these findings, the study proposes targeted resilience enhancement strategies. In resource-constrained environments, a phased and prioritized approach is recommended, focusing on strengthening infrastructure, improving ecological conditions, optimizing population composition, enhancing economic stability, reinforcing organizational systems, and promoting cultural awareness. These measures aim to systematically improve disaster resilience in urban old communities and provide a solid foundation for community-level disaster preparedness and response.