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Exact(10)
Second, the contributions of two factors, namely EC effectiveness and EP model, are quantified on dataset-2.
The predictions of the model are quantified with the aid of a computer simulation and compared with the experimental results.
Deviations from a linear model are quantified statistically by generating surrogate data sets that, by construction, possess only linear (second-order) correlations.
The resulting (upscaled) continuum-scale system of equations includes nonlocal integro-differential terms and the effective parameters embedded in the model are quantified directly through computed pore-scale fluid velocity and pore space geometry attributes.
In the Bayesian approach, prior knowledge about parameter values in a statistical model are quantified in terms of prior probabilities.
Applying an innovative method, the parameters in the model are quantified by an adjusted Delphi approach using expert knowledge.
Similar(50)
On the abscissa, the coefficient value for the variable in the linear regression model is quantified.
Then, the information flow of the model is quantified using Conant's model.
In this method, the uncertainty in the rate parameters of the as-compiled model is quantified.
The accuracy of an approximate linear model is quantified by the use of an average relative error.
The performance of the model is quantified through a series of experimental studies involving synthetic and real-world data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com