Sentence examples for model validation studies from inspiring English sources

The complete data are available on the World Wide Web for use in model validation studies.

The model validation studies on an experimental system show that the model predicts the system dynamic well.

For those studies, one new C amount was used for model selection and parameter optimization (studies 8, 34, 36, and 42 in Supplementary Data 1; training group), and the others were used for model validation (studies 9, 10, 35, 37, and 43 in Supplementary Data 1; validation group).

This contribution evaluates the impact of instrument uncertainties contributing to data inaccuracies and their effect on short-term and long-term measurement series, and on radiation model validation studies.

In the vast majority of the turbulence model validation studies we review, the authors fail to adequately address the numerical accuracy of the simulations (i.e., discretization and iterative error) and the sensitivities of the model predictions to freestream turbulence quantities or near-wall y+ mesh spacing.

Nine rabbits were used for model validation studies.

A dispersion model validation study is presented for atmospheric releases of dense-phase carbon dioxide (CO2).

When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis.

Eight adjustable modeling parameters are estimated from experimental data from a prototype system, and a model validation study shows that predictions of water venting rates and of cell voltage have errors better than 9% when extrapolating to conditions not used for parameter estimation.

Plot at the top is from the model validation study and shows the evolution of voltages at all 20 buses; these voltage time series are in good agreement with those observed in the corresponding cascading voltage collapse for the actual grid.

The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.