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This distribution takes into account both parameter and structural uncertainty in the final output results of the prediction model.
In this case study, results of the uncertainty propagation of both parameter and structural uncertainties are shown in Fig. 14.
As a result of these new opportunities, evolutionary algorithms have been applied to controller design and model identification, for both parameter and structural optimisation and for handling multiple competing performance objectives.
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The main objective is to test the impact of parameter and structural uncertainties.
Figure 7 shows possibility distribution representing integrated parameter and structural uncertainty through the LCC prediction modeling.
This study has proposed an approach for reducing parameter and structural uncertainty in LCC prediction modeling.
Parameter and structural uncertainty were explored in sensitivity analyses.
With respect to the analysis of sensitivity, the extraction refers to parameter and structural uncertainty.
The experimental study on the influence of modulation parameters and structural parameter was carried out.
Table 1 summarizes the deposition parameters and structural responses used in the present study.
The effects of wave parameters and structural parameters on the second-order nonlinear wave forces are studied.
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