Dependency network mapping
Suppliers, infrastructure services and counterparties are recorded as a directed network, with link types and buffers, so that paths from any failure to critical services can be traced.
GCRI · 系统性风险管理
Network science represents 系统 as nodes and links so that the structure of dependence can be measured. In 系统性风险 management it maps how organisations, infrastructures and suppliers connect, identifies central and concentrated nodes, and simulates how failures propagate through the structure.
Network science and contagion study how the structure of connections among entities shapes the spread of failures, information and disease. It provides tools to analyse interdependent infrastructure, supply chains and financial 系统. In risk management and 系统性风险 and methods and modelling, network science identifies critical nodes and pathways through which shocks propagate across sectors. It informs targeted protection and diversification to limit cascades. The canonical description is on STEM Commons.
Suppliers, infrastructure services and counterparties are recorded as a directed network, with link types and buffers, so that paths from any failure to critical services can be traced.
Measures such as betweenness and degree identify nodes on many paths or with many dependants, which become candidates for redundancy or closer oversight.
Threshold and load-redistribution models simulate how removing one or several nodes spreads failure, showing which combinations cause the largest loss of service.
Population density, flood water and night lights over Asia, from NASA GIBS. Each layer carries its own date.
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页面的危害与暴露
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最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
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危害与风险暴露,以亚洲为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by network science and contagion on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Dependency inventories from operators | Network structure | 已声明 |
| 投入产出表 | Industry-level dependencies | 已发布统计 |
| Procurement and supplier records | Firm-level links | 观测 |
| Infrastructure network data | Physical connections | 已发布统计 |
两个存量,即压力和 适应能力,由一个增强型增长回路、一个延迟的平衡响应以及压力超过能力时的损害连接在一起;越过阈值后,系统可能发生突变。这是带有说明性取值的教学模型,不是预测。本页地图显示亚洲;模型本身并不绑定某个地点。
控制措施
读数
| 年份 | 压力 | 能力 | 感知 |
|---|---|---|---|
| 0 | 20.0 | 50.0 | 20.0 |
| 4 | 23.3 | 44.9 | 21.2 |
| 8 | 27.2 | 42.2 | 24.0 |
| 12 | 31.7 | 42.3 | 27.7 |
| 16 | 36.8 | 45.5 | 32.2 |
| 20 | 42.3 | 51.5 | 37.2 |
| 24 | 47.9 | 60.3 | 42.6 |
| 28 | 53.2 | 71.3 | 48.0 |
| 32 | 57.8 | 84.3 | 53.1 |
| 36 | 66.4 | 98.4 | 58.4 |
| 40 | 82.7 | 115.9 | 69.7 |
| 44 | 97.8 | 139.7 | 83.8 |
| 48 | 109.1 | 169.4 | 97.3 |
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱,由 Nexus Consortium 牵头
Models are checked by reproducing observed cascades and outbreaks. Robustness of results to missing or uncertain links is tested.
| 核查 | 如何开展 |
|---|---|
| Missing link sensitivity | Results are recomputed with links randomly added or removed to test sensitivity to incomplete data |
| Validation against past events | Simulated propagation is compared with documented cascades |
| Alternative failure rules | Different propagation rules are tested and the spread of results reported |
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
Assembled from the Nexus Standards area profile 全球与系统性风险: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
灾害
控制措施
NS-0 章程与原则NS-3 风险记录 UNI(语法、旧编码对照、分配机构)NS-9 情境 UNI(部署、实例、计划实例)NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)NS-11 验证与监测(证据、证明、零信任符合性观测)NS-14 符合性及与外部标准的对照NRS-H120 危害族:互联系统的结构性脆弱(NHS-1 sys.fragility)NRS-C6 系统性风险与级联风险NRS-H61 危害族:级联失效(NHS-1 sys.cascade)NRS-H62 危害类别:复合与多危害事件(NHS-1 sys.compound)NRS-H94 危害族:系统性网络事件(NHS-1 cyber.systemic-cyber)NRS-H60 危害类别:供应链与流动中断(NHS-1 sys.supply-chain)观测
示例地理范围
模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。
The model structure used for network science for systemic risk, the assumptions it makes and how each is tested.
Ri = f(Hi, Ei, Vi, Ci)危害、风险暴露、脆弱性和应对能力EAL = ∑k pk · Lk对年概率为 pkxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| 假设 | 为何制作 | 如何检验 |
|---|---|---|
| 在一次事件中,危害与暴露相互独立 | 使损失积分保持可计算 | 与基于联合记录拟合的 copula 进行比较 |
| 耦合在工作点附近是线性的 | 让冲击通过 A 传播 | 在线性范围之外施加扰动并比较 |
| 脆弱性曲线可以在不同地点之间迁移使用 | 很少有本地曲线可用 | 在有观测损失的地方据此进行验证 |
系统科学与建模 stewards network science and contagion for the Consortium and reviews how it is applied across platforms.
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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