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I think it is the concept of Lenovo machine, or even just a model can not be changed.
Compared to numerical and analytic methods, this model can not only reduce extensive computing processing but also show high accuracy.
But our model can not predict lower critical solution temperature (LCST) behaviours of liquid liquid equilibria for binary polymer solutions.
The model can not only generate the signal as expected, but also provide explicit control parameters for online modulation.
The sucrose rejection factor was found to be greater than 98.9% and therefore the response surface model can not be developed for this response.
The developed GFIPMIP model can not only forecast electric demands, but also reflect dynamic, interactive, and uncertain characteristics of the IEEM system in Beijing.
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Existing Finite Element models can not predict edge fracture with good accuracy.
Furthermore, other neural networks models can not provide a certain equation for managers to use.
The UNIQUAC/UNIFAC models can not in general represent vapor-liquid and liquid-liquid equilibria simultaneously with satisfactory results.
It is shown how feature models can not only describe arbitrary RAPs but also much more complex design problems.
However, the traditional mesh simplification methods for graphical models can not satisfy the requirements of CAD mesh simplification.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com