Sentence examples for underlying process model from inspiring English sources

Therefore, we instead made inferences using posterior distributions of model parameters and underlying process model predictions.

In a standard optimization approach, the underlying process model is first identified at a given set of operating conditions and this updated model is, then, used to calculate the optimal conditions for the process.

A method is developed to solve an optimal node activation problem in sensor networks whose measurements are supposed to be used to estimate unknown parameters of the underlying process model in the form of a partial differential equation.

Hazard assessments are based on information of past activity (from the geological and historical records), and the understanding of underlying processes and models.

This indicates that the trained SCCS model successfully approximates the compound underlying process within the target sea clutter.

Close inspection of the underlying processes in the model suggest that this is likely due to a greater D1R inhibition (by the 9-OH risperidone metabolite) and greater presynaptic 5-HT1BR inhibithat tend tond to increase free 5-HT and activate 5-HT4, 5-HT3, and 5-HT6R.

We could opt for greater realism and represent these underlying processes in our model at a more detailed, lower organizational level, such as the scale of individual plants and seeds, in what might be called a bottom-up approach (Fig.  1, Approach 2).

While we believe the assumptions provide results sufficiently approximating the underlying processes, in a joint model it would be worth including the uncertainty about withdrawal as an interval-censored time variable, and this has not been done before.

For many problems in cellular control, stochastic effects and time-delays can be ignored and systems of first-order ordinary differential equations (ODEs) can adequately model the underlying processes.

Inherent to mathematical modelling, assumptions must be made about the underlying processes that are incorporated in the model.

By directly modeling the underlying processes, a biophysics-based approach can overcome many limitations of the statistical methods mentioned above.