Sentence examples for model approximation process from inspiring English sources

This model approximation process is summarized in the Methods.

Then, the DPL-model can be written as (17) where A kl is a 2 × 2 matrix, B = (k1 0)', C = (1 -1), k1 a constant parameter, and the following rules are used for switching between linear systems (18) Here θ25/ wee, θ slp / ste and τ are constant parameters retrieved from the model approximation process.

The original Novak and Tyson model [ 19] which was our point of departure corresponds to (3) (4) (5) (6) (7) (8) (9) (10 1112) (13) (14) (14) where (15) The default parmater values corresponding to the wild-type cell are (16) The hybrid model approximation process is described in [ 15] and summarized further down.

In the present work, the straight method of nonparametric model approximation was accepted and the calculation algorithm process is as follows.

In combination with an incremental learning approach such as incremental Gaussian process regression, we obtain a model approximation method which is applicable in real-time online learning.

The translation was done using a recalibration process, adapting the hybrid model to the original perturbed one through re-performing the hybrid approximation process and measuring the effect of the perturbation on for all m = 1... n hyb (Methods).

We then use a Gaussian mixture model approximation to estimate a weighting scheme of in order to account for the initialization process when recombining samples from different modes.

The comparison with a more rigorous model also exposes subtleties about the effect of model approximations on the predicted process performance, in that the cancellation of the effects of certain simplifying assumptions results in near quantitative agreement with the more rigorous model, in some cases.

The first approach is to employ approximations at various levels of the modeling and simulation process.

Gaussian process emulators of computationally expensive computer codes provide fast statistical approximations to model physical processes.

Step 3: Model selection process.