论文标题
具有非线性动力学的复杂网络中弹性的不确定性
Uncertainty of Resilience in Complex Networks with Nonlinear Dynamics
论文作者
论文摘要
弹性和错误发生时，弹性是系统保持其功能的能力。尽管我们很好地了解了低维网络系统的行为，但我们对由大量组件组成的系统的理解是有限的。在预测网络水平弹性模式方面的最新研究使我们对全球网络拓扑与本地非线性组件动态之间的耦合关系的理解提高了我们的理解。但是，当模型参数存在不确定性时，对于大型网络系统而言，我们对这如何转化为弹性不确定性的理解尚不清楚。在这里，我们开发了一种多项式混乱扩展方法，以估计对多种不确定性分布的弹性。通过将此方法应用于案例研究，我们不仅揭示了有关拓扑和动态子模型的一般弹性分布，而且还确定了关键方面，以告知更好的监测以降低不确定性。
Resilience is a system's ability to maintain its function when perturbations and errors occur. Whilst we understand low-dimensional networked systems' behavior well, our understanding of systems consisting of a large number of components is limited. Recent research in predicting the network level resilience pattern has advanced our understanding of the coupling relationship between global network topology and local nonlinear component dynamics. However, when there is uncertainty in the model parameters, our understanding of how this translates to uncertainty in resilience is unclear for a large-scale networked system. Here we develop a polynomial chaos expansion method to estimate the resilience for a wide range of uncertainty distributions. By applying this method to case studies, we not only reveal the general resilience distribution with respect to the topology and dynamics sub-models, but also identify critical aspects to inform better monitoring to reduce uncertainty.
