Suppr超能文献

一种集成熵云与模糊认知地图的CAS驱动框架增强了城市老旧社区的灾害恢复力。

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

作者信息

Liang Weijing, Xue Ye

机构信息

College of Economics and Management, Taiyuan University of Technology, Taiyuan, 030024, China.

School of Economics and Management, North China University of Science and Technology, Tangshan, 063210, China.

出版信息

Sci Rep. 2025 May 6;15(1):15804. doi: 10.1038/s41598-025-98278-4.

Abstract

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.

摘要

城市人口和资产的高度密集加剧了自然和人为灾害带来的风险,给防灾和应对工作带来了严峻挑战。这些挑战在城市老旧社区尤为突出,因为这些社区往往缺乏足够的抗灾能力和适应能力。本研究聚焦于城市老旧社区,借鉴复杂适应系统(CAS)理论和社区恢复力的概念,探索支持恢复力提升的资源系统。构建了灾害恢复力评估指标体系,并采用熵权法结合云模型来评估当前的恢复力水平。识别了影响恢复力的关键因素,并应用模糊认知图(FCM)模型模拟其动态相互作用和影响机制。结果表明,城市老旧社区的灾害恢复力较低主要源于基础设施老化、生态系统脆弱、人口结构失衡、经济不稳定、组织能力不足以及文化意识淡薄。其中,基础设施恢复力和文化意识是最关键的因素,是提升恢复力的关键途径。基于这些发现,本研究提出了有针对性的恢复力提升策略。在资源有限的环境中,建议采用分阶段、按优先级的方法,重点加强基础设施、改善生态条件、优化人口构成、增强经济稳定性、强化组织系统以及提升文化意识。这些措施旨在系统地提高城市老旧社区的灾害恢复力,为社区层面的防灾和应对工作奠定坚实基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e9d/12056038/d0841cb36397/41598_2025_98278_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验