herkkäystoiminnastaarviointi

Herkkyystoiminnastaarviointi, often translated as sensitivity analysis, is a method used in various fields to determine how the uncertainty in the output of a model or system can be attributed to different sources of uncertainty in its inputs. It involves systematically varying the input parameters and observing the resulting changes in the output. This helps in understanding which inputs have the most significant impact on the model's predictions or the system's behavior.

The process typically begins by identifying the key input variables and their associated uncertainties, often expressed as probability distributions or ranges. Then, a series of model runs are performed, where these input variables are changed according to a pre-defined plan. The results of these runs are analyzed to quantify the sensitivity of the output to each input. Common techniques include one-at-a-time (OAT) analysis, where each input is varied while others are held constant, and global sensitivity analysis methods, which consider the interactions between multiple inputs simultaneously.

The outcomes of sensitivity analysis are valuable for several reasons. It helps in identifying critical parameters that require more accurate data or careful control. It can also highlight redundant or unimportant parameters, potentially simplifying the model. Furthermore, it aids in risk assessment by understanding how uncertainties in inputs translate to uncertainties in outcomes, and it can guide future research by focusing efforts on areas with the greatest potential impact. Sensitivity analysis is widely applied in fields such as environmental modeling, engineering, economics, and climate science.