Description:
The analysis of uncertainty and sensitivity of various modeling results includes a comprehensive assessment of the accuracy, reliability, and risk of simulation models, taking into account the uncertainty of data, initial conditions, and parameters. The analysis identifies how various factors influence model predictions, assesses risk aspects, and evaluates possible scenarios for system behavior. Sensitivity analysis allows the identification of the parameters that most influence the results, while uncertainty analysis helps to determine the limits of reliability of the model results. This assessment makes it possible to select effective uncertainty control measures, optimize decision-making, and increase the predictability of model-based processes.

Field of Science:
ICT technologies, inclusive and creative society, Health technologies, biotechnologies and safe food, New production processes, materials and energy efficiency