Sentence examples for model prediction can from inspiring English sources

The NN model prediction can be implemented for online application such as rolling schedule optimisation and dynamic roll gap control, due to its fast calculation ability.

By enforcing a certain level of robustness, the variation in the model prediction can be reduced, which overcomes the major weakness of the traditional probabilistic approaches that focus solely on model fidelity.

For the first case (i.e. large ψ) it is found that the conversion correction to the shrinking core model prediction can be significant even for reasonably large values of ψ, and the error is as serious as that found in Part I for moderate diffusional resistance.

Given the fact that the mechanistic model simulation was based solely on physical parameters reported in the literature without employing any curve fitting, the agreement between the experimental data and model prediction can be considered as quite good.

B I C = 2 (L C N A + L B A F + L S N V ) − k log (L C N A + L B A F + L S N V ) k ≡ (c m a x + 1 ) n + N s (n + 1 ) Additionally, the goodness of fit (the average geometrical distance of data points to the model prediction) can also be used as a model comparison criterion and is included in the output.

Model predictions can be improved by considering the through-thickness fracture behaviour of the coating.

Model predictions can be evaluated during pilot-testing that often precedes microfilter regulatory approval and plant design.

The model predictions can be used to improve the design of composite electrodes for solid oxide fuel cells.

This implies that the model predictions can be generated prior to synthesis of these structures and their adsorption affinities can be evaluated entirely in silico.

Due to the inherent uncertainties in combustion kinetic model parameters, especially the rate coefficients of elementary reactions, the uncertainties of model predictions can be quite large.

A virus dynamics example shows that the dynamical statistical model predictions can be more accurate than both the black box statistical model predictions and a coarse numerical solution of similar computational order.