An Empirical Monte Carlo Simulation Framework for Risk Assessment and Uncertainty Quantification in Complex Stochastic Systems
Complex stochastic systems are shaped by uncertain input variables, nonlinear interactions, and low-probability failure events that cannot be adequately summarized by deterministic point estimates. This study develops and empirically evaluates a Monte Carlo simulation framework for risk assessment and uncertainty quant...