一个集成云和模糊认知地图的CAS驱动框架增强了城市老社区的灾难适应能力
Weijing Liang1,2, Ye Xue3
1College of Economics and Management, Taiyuan University of Technology, Taiyuan, 030024, China. liangweijing99@163.com.
Scientific reports
|May 6, 2025
概括
城市老社区面临着严重的灾害风险,原因是基础设施老化和系统薄弱. 提高基础设施弹性和文化意识是改善这些脆弱地区防灾准备和应对的关键.
科学领域:
- 城市规划和灾害管理
- 社区性研究研究.
- 复杂自适应系统 (CAS) 理论
背景情况:
- 人口密集的城市地区的灾害风险增加,特别影响脆弱的老年社区.
- 城市老社区往往表现出对自然灾害和人为灾害的抵抗力和适应能力不足.
- 需要一个系统的方法来评估和增强这些特定的城市环境中的抗灾能力.
研究的目的:
- 利用复杂适应系统 (CAS) 理论,探索支持城市老社区恢复能力增强的资源系统.
- 开发和应用一套防灾能力评估指数系统,以评估当前的防灾能力水平.
- 识别关键影响因素及其动态相互作用,以制定有针对性的弹性战略.
主要方法:
- 开发一个灾难适应能力评估指数系统.
- 应用重法和云模型用于弹性评估.
- 使用模糊认知地图 (FCM) 来模拟影响因素的动态相互作用.
主要成果:
- 确定了导致抗灾能力低下的关键因素:基础设施老化,生态系统脆弱,人口不平衡,经济不稳定,组织不足和文化意识有限.
- 基础设施弹性和文化意识被发现是提高弹性的最关键因素.
- 该研究强调了各种社区系统在确定整体抗灾能力方面的相互联系.
结论:
- 针对资源有限的环境提出了有针对性的策略,强调分阶段和优先级的方法.
- 建议包括加强基础设施,改善生态条件,优化人口结构,增强经济稳定,加强组织能力和促进文化意识.
- 该研究提供了一个框架,用于系统地提高城市老社区的抗灾能力,提高准备和应对能力.
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