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Figure 12 Model prediction results in terms of solids content profiles.
Figure 9 Model prediction results in terms of excess pore water pressure profiles.
Figure 11 Model prediction results in terms of void ratio profiles.
Figure 10 Model prediction results in terms of effective stress profiles.
The proposed model prediction results were in good agreement with the experimental results.
The model prediction results are in good agreement with the field observations to date.
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Fig. 8 SVM classification based on credit risk assessment model prediction result.
Also, we evaluate the potential for improved model prediction resulting from the use of geographic covariates with higher spatial resolution than those used previously for traffic density, population density, and point-source emissions density.
This diversity impacts estimated asthma prevalence rates and the models' prediction results [ 176].
For classification models, prediction results were reported by calculating the overall accuracy (ACC, proportion correct), the balanced error rate (BER), the area (AUC) under the receiver operating characteristic (ROC) curve, and the RF out-of-bag (OOB) error rate.
Experimental verification of the model predictions resulted in a 65% improvement in titer, to 40.7±0.1 mg/L flavan-3-ols, over the previous optimum.
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