Sentence examples for more simple models from inspiring English sources

Elaborated non-linear finite element models are used in order to verify the quality of the results obtained from more simple models used in everyday engineering practice.

These more simple models only take into account, separately, the Listener brain-audio entrainment (Model 1) and the Speaker brain-audio entrainment (Model 2) and could be important in explaining results in the brain-to-brain entrainment that go unnoticed in the main full model.

In this new, more robust model of BGP behavior, we derive a necessary and sufficient condition for safety, which furthermore admits an efficient algorithm for checking BGP safety in most practical circumstances - two complementary results that have been elusive in the past decade's worth of classical studies of BGP convergence in more simple models.

The ARIMA model performs best, followed by the trimmed-mean seasonal model and the other more simple models.

If we are to use models of intermediate complexity as a bridge, we must also connect and relate them to the more simple models mentioned above (Barton 1979; Turelli and Hoffmann 1991; Schofield 2002; Soboleva et al. 2003; Turelli 2010).

For each model, an r-value quantifies the variance explained by the model and an F-value quantifies the model significance, which takes into account the number of independent variables in order to favour more simple models.

The more simple model is therefore preferred for the expression of i-E curves of zinc deposition.

A more simple model is probably sufficient but the same model is kept in order to view AA, AM and AR simultaneously.

Indeed, the more simple model variant EA (analysed in the previous section) proved to be highly succesful in dealing with small-size HP protein sequences.

In this way, the authors investigated if a more simple model 1 with an APACHE score had better discriminative power than a more complex model 2 where the APACHE score was omitted but physiological patient variables were added.

In this paper, we present a simple, yet intuitive, criterion for choosing between two quantile regression models: select a more complex model over a more simple model if the ratio of the RSADs of the two fitting models is smaller than a predefined threshold.