Sentence examples for models have often from inspiring English sources

Since the seventies these models have often been solved with spectral methods.

Recent models have often been tepid reinterpretations of existing (and cheaper) Ford-badged alternatives.

Although pore-flow models have often been applied to describe membrane performance, it is difficult to obtain some key parameters, including the transport-active pore size distribution, which is a governing characteristic in determining the selectivity.

Generalized models have often been used without consideration of the tree age or plantation age.

Physiologically inspired macroscopic brain models (for example neural mass and neural field models) have often been employed to investigate the causes of epilepsy and seizures [3 8].

Such models have often had to rely upon informed guesses for parameters describing the soil moisture and air temperature growth response functions.

So far, extremity ischemia and subsequent neovascularization-guided perfusion recovery in animal models has often been evaluated by predominantly anatomic (MRI), invasive (angiography), or limited (LDPI) techniques.

The performance of LR models has often been compared to that of BL classifiers in discrimination problems.

While this does not of itself mean change is impossible, in most countries supporters of the model have often sacrificed attempted reforms on the altar of "social cohesion" (see article).

In recent years, reliability analysis methods based on the Kriging surrogate model have often been employed to obtain accurate failure probabilities of problems since the Kriging model can be used to provide predictions of the performance function at sample points and the corresponding variance of these predictions.

Previous attempts to re-express (M,R) in mathematical terms that might be more conducive to construction of a Turing computable model have often met with the response that they misrepresent in some way the structure of (M,R).