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Simulations predict Δ Φ uniquely according to the model parameters thus constrained, but the absolute level of strength does not affect the simulated behavior at all.
This process-based concept has the advantage of requiring only measurable model parameters, thus avoiding fitting parameters like first-order rate coefficients.
Model parameters thus obtained were subsequently used as constraints to quantify the CMT processes involving Co II EDTA and its oxidation product Co III EDTA.
In this paper, a disturbance estimation approach is exploited within an OMBRE framework (DEOMBRE) in order to achieve a statistically satisfactory estimation of the model parameters, thus avoiding (or reducing) constraint violations even in the presence of systematic modelling errors.
The data of Figure 5A were not used to estimate model parameters; thus the model predictions in Figure 5A represent validation of the overall model based on the prediction of how relative activity increases with [Mg2+] in the presence of ATP.
All these structural changes will introduce more state variables and model parameters, thus nothing would be gained by these efforts without the generation of accurate quantitative data to pin down both the model structure and the parameter values.
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We have devised a model that retains much of the intrinsic geometric configuration of the system, and thus fewer laboratory experiments are needed to determine model parameters and thus to develop new optimized cryopreservation protocols.
By this approach the RCC model parameters, and thus the AR parameters are estimated.
Compared to previously introduced controllers, the proposed control law does not depend on model parameters and thus is robust to system uncertainties.
Our hypothesis is that by enabling each training sample to influence multiple sets of model parameters (and thus cover a larger portion of contextual space), generalization to unseen contexts would be improved.
When using the Gauss Newton method for automatic history matching problems, Wu et al. (1999) introduced an artificially high variance of measurement errors at early iterations to damp the changes in model parameters and thus avoid undershooting or overshooting.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com