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The philosophy behind this modeling approach and its major commonalities and differences with numerical and analytical models are explored and two different categories of such models are explained.
Some special models are explored.
To leverage the available tools for LTI IMC design, the quasi-linear parameter-varying (quasi-LPV) models are explored.
In this paper, a number of models are explored to understand what should be the best approach for collecting and storing Big Data for analytics.
In particular, various turbulence models are explored to assess their effectiveness to capture the separated wake flow dynamics behind the square cylinder.
The solution properties of the proposed models are explored and compared analytically, and the indifference condition for the two fare regimes in terms of the operator's net profit is identified.
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These numbers of models were explored in order to present a robust overview of possible estimations.
In addition, the applicability of the two beam models is explored by numerical simulations.
Multivariate regression models were explored for non-destructive determination of date, tensile strength, pH and DP (Table 2).
In light of these observations, sphere close packing models were explored.
Furthermore, the application of the papiNet standard with these data models is explored.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com