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Continuous, discontinuous, and random models of belt velocity were considered.
The curve on the left side represents the distribution of AUC ratios for random models.
Figure 7 shows that using three random models of the same accuracy opens multiple possibilities regarding accuracy improvement.
These suggestions provide a basis for new studies and these options for random models will be evaluated in new papers.
Percolation thresholds are greater in the random models; it is observed that the greatest difference occurs at low pore connectivities.
Fundamental issues are to estimate certain parameters (i.e., deterministic quantities) appearing in the random models by certain observations (or by experimental data).
In Fig. 5, the envelope for aggregating one accurate model at 89% accuracy with two random models of the same accuracy is displayed.
The explanatory variables (x_{t}) are generated by the following two random models: I. (x_{t}=5mathrm{u}_{t}), (1leq t leq n); II.
The random models consist of 3-D domains of 216, 512 or 1000 cells with periodicity conditions on the compressed ends but free on the sides.
Results showed the importance of the selection of random models and the use of FEA for predicting the Young's modulus of reinforced metallic foams.
Last, we determined that phrase order, although diverse, deviated from random models.
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CEO of Professional Science Editing for Scientists @ prosciediting.com