Sentence examples for primary model parameters from inspiring English sources

The effect of primary model parameters including particle size (ap) and particle concentration (C0), were accurately assessed without any fitting parameters, and the MFI values predicted by the model exhibited very good agreement with the experimental results.

In predictive microbiology, the model parameters have been estimated using the sequential two-step modeling (TSM) approach, in which primary models are fitted to the microbial growth data, and then secondary models are fitted to the primary model parameters to represent their dependence with the environmental variables (e.g., temperature).

During those tests the two primary model parameters, fm and rm which control the mixing distance between particles in both mixture fraction space and physical space, are held constant so that those mixing distances are independent of the number of particles used and, at the same time, the sparse character of the mixing model is preserved.

LIPSSS-based estimates for the primary model parameters under all experimental conditions are shown in Figure  4.

The so-called secondary models describe the relationship of primary model parameters to varying experimental conditions, like, for example, temperature.

The primary model parameters derived were plasma clearance (CL) (in liters/h/kg), intercompartmental clearance (Q) (in liters/h/kg), central and peripheral volume of distribution (Vc and Vp, respectively) (in liters/kg), and the absorption rate constant (Ka) (in h−1).

Each key parameter in the dictionary model and its influence on the analysis results are systematically studied, and the impulse location is determined as the primary model parameter.

The effects of temperature on the primary-model parameters were well described by the Kohler, Ratkowsky, asymptotic and non-linear Arrhenius models.

Hypotheses were tested based on the estimated model parameters; of primary interest was the overall test for interaction among the three chemicals.

A logistic regression model and a discriminant analysis model were made as two primary models with the parameters of "gender" and "manifestation".

A three-parameter Weibull primary model was used to describe survival kinetics.