Modern Critical Infrastructures (CIs) are typically characterized by a large number of elements interconnected and interdependent (Kröger and Zio, 2011). Their mathematical representation reflects these characteristics in models that typically turn out to be: 1) complex, since the relation between the variables can be nonlinear; 2) large, since a high number of variables is typically involved in the model; 3) dynamic, because the behavior of the system evolves in time. For this reason, the opportunities of exploring these models in order to extract information, such as identifying the most critical events, is conditioned by the computational cost of a simulation run and by the number of variables to explore (Santner et al., 2003).
|Titolo:||Dimensionality reduction of the resilience model of a critical infrastructure network by means of elementary effects sensitivity analysis|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||04.1 Contributo in Atti di convegno|