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The results between experiment and model simulation will be compared for model validation.
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Both the simulation and the experiments were done for several cases and results of the same operating conditions from both platforms were compared for model validation as well as system performances.
A Bland-Altman plot was drawn and the two equations were compared for model fitting using R-squared.
Predicted group assignments were compared for models in which severity measures were made with whole-word repetitions excluded or included.
In this paper, two geostatistical approaches are compared for modeling the Rock Mass Rating (RMR), which is used to geomechanically characterize the rock mass in geotechnical works.
The estimates, ˆμ and ˆVar, were compared for models constructed using calibration and application data of the same date and models constructed using calibration and application data whose dates differed.
Residual model deviances were compared for models in which benzene exposure acted upon the first, second, third, or fourth stage of a five-stage disease process (Table 5).
The AIC values were compared for models with and without putative outliers (process two) and the best model included 17 samples (indicating RudP, Ash, Gata, RudB and RudC were true outliers; Table 4).
The performances predicted by the two models were compared for various model parameters – GDL porosity (0.6 and 0.9), GDL tortuosity (1.5 and 2.5), and coefficient of water vapor condensation rate (500 s−1 and 5000 s−1).
The three sets of model runs were compared for between-model consistencies.
For the multivariate logistic regression analyses, the c-statistic and the Hosmer-Lemeshow Goodness of Fit test are compared for each model.
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CEO of Professional Science Editing for Scientists @ prosciediting.com