Monte Carlo simulation (2)

The answer can be found in calculating uncertainty propagation. Uncertainty propagation is increase or decrease of input parameter uncertainty pictured over deterministic model on output values of model.

Figure 2: Picturing input parameter in statistical distribution shape in output value over a one dimensional model

If the model is more complicated, the uncertainty propagation cannot be solved directly, but using certain uncertainty estimation techniques. Some of them are: Monte Carlo, First Order Second Moment, Bayesian method or fuzzy set a cut method.

Figure 3: Uncertain input parameters and uncertain output parameters

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