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The MLF model gave good predictions for both experimental and surface complexation-model predicted datasets for these two sorbents.
Predictions for both ILRR and DR were partly well calibrated but the predicted percentages were unsatisfactory when both low-intermediate and HR women were studied (Table 3).
ABC has aggressively sought a way to gather data necessary to make predictions for both television and online viewing.
The observations contradict the predictions for both models.
The predictions for both phenomena agree well with experimental data.
The SIMCA modelling approach results in 100% correct predictions for both calibration and validation sets.
Figure 4 plots the normalised RMSE (NRMSE) of the predictions for both datasets.
In Figure 8, we can compare the accuracy of the predictions for both algorithms.
However, using multi-objective optimization, good predictions for both streamflow and LAI are obtained.
Activity vs foulant weight data are compared to model predictions for both inactive and active fouling.
The predictions for both criteria fell within a 15% scatter band.
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