A novel approach to characterizing the risks and agility in any complex system of systems

This work describes a method to characterize the risk, agility and resilience of any complex system of systems. The algorithm uses a rigorous approach to estimate initial parametric sensitivities between any and all defined variables to include temporal dependencies. The published version (Hayes 2022) demonstrated this capability using only toy models with sufficient generality to expect that this can apply to any complex interconnected system of systems. The goal being to provide decision makers with a tool to predict outcomes based on various choices of corrective actions on their part in large scale emergencies, national crisis or other scenarios of substantial consequence. The approach is capable of standalone operation when initialized by expert opinions on system iterdependencies and sensitivities but is amenable to optimization by fitting it to real world data using machine learning with big data.

Hayes, R. B. (2022). A systems approach to a resilience assessment for agility. Systems Science & Control Engineering, 10(1), 955-964.