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It is notable, however, that unpredictable results that might be obtained with the use of uncertain input are not without their practical application.
Twelve uncertain input parameters were selected.
This TIB simulator depends on many uncertain input parameters.
Often, the modeling process covers large spatial and temporal intervals with many uncertain input parameters.
The proposed methodology does not require any probabilistic information on uncertain input parameters.
The influence of uncertain input data on response spectra of dynamic structures is considered.
Monte Carlo simulation handles uncertain input parameters as random variables based on given probability distributions.
The method considers a nonlinear relation between the uncertain input and the constrained variables.
Uncertain input parameters in our model are the CNT waviness, agglomeration, applied load and FE discretization.
However, design problems typically rely on uncertain input data, such as future energy demands or prices.
Main conclusions on the influence of each uncertain input are derived.
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