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The average Kriging prediction error and cross-validation methods are used to validate the robustness of the produced model of the initial experimental design which is found to highly affect the final predicted feasible region.
ROC analysis using the cross-validated predicted Y (predicted class) values was performed to validate the robustness of the OPLS-DA model.
Various numerical examples are tested to validate the robustness of the proposed FESF model.
Further, an experimental data is used to validate the robustness of the formulated GP model.
Experiments are further performed to validate the robustness of the models.
Two different cases are examined to validate the robustness of IMC based controller design.
The simulation and experimental results can validate the robustness of this proposed method.
Various numerical tests concerned with the shock instability are performed to validate the robustness of the proposed scheme.
Sensitivity analysis on the selection of prior distribution is also performed to validate the robustness of the proposed Bayesian AASPs.
Flow problems with and without physical diffusion are employed for the numerical tests to validate the robustness, accuracy, and consistency of the proposed approach.
To validate the robustness and applicability of the proposed new model, we reproduce the shape memory behaviors (SMBs) of two different materials under different constraints and conditions.
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