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As shown in Fig. 3, the plot of intra-particle diffusion model given a straight line to the data obtained with R2 greater than 0.9.
As mentioned before model selection bias can be envisaged as underestimation of the true prediction error of a particular model given a particular data set just by chance.
Based on the proposed model, given a finite retry limit, the minimum window of a vehicle can be determined according to its velocity.
By additionally defining a prior density over, we can try to find the maximum a posteriori (MAP) model, given a set of observation sequences (4).
As shown in Fig. 2, the plot of Weber Morris model given a straight line to the data obtained with R 2 greater than 0.8.
Single phase flow phenomena are nowadays fairly easy to model given a good representation of the porous medium by its digital counterpart.
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The logistic model gave a correct prediction in 73%to83%3%.
The model gave a coefficient of determination (R2) of 0.87.
This model gives a process transfer function (Laplace domain).
The model gives a good prediction of the paraffin distribution.
The proposed model gives a better agreement with these experimental results compared to previous models.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com