Sentence examples for variability of the models from inspiring English sources

This work presents a study of an ensemble-based method, derived from the Kalman Filter (KF), the Ensemble Smoother with Multiple Data Assimilation (ES-MDA), in conjunction with a localization technique applied to a benchmark model with a known response, seeking to evaluate the final variability of the models and potential exclusion of better models in a HM problem.

This lack of progress is mainly because of the unstable nature of L-form bacteria, the variability of the models used for their generation, and the unavailability of modern molecular biology tools before the 1980s when L-form research was largely abandoned.

The variability of the models suggests the need for the arrangements to be flexible.

An impressive body of evidence has been obtained in preclinical studies using in vivo CRC models, consistently supporting the antineoplastic role of omega-3 PUFA [ 8, 154, 172], in spite of the high variability of the models and experimental conditions used [ 134, 135, 154, 173, 174].

The variability of the model under a moderate amount of stochastic forcing, meant to emulate the random variability of the atmosphere affecting the coupled model's interdecadal THC variability, is studied.

The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters.

Furthermore, this paper presents different combinations of lead-time and demand scenarios to demonstrate the variability of the model.

How to characterize the cross-site variability of the model bias factor is important for design of pile foundations based on site-specific load test data.

PTFs could explain 12 48% of variability of the model's parameters, and the inclusion of topographic attributes (i.e. SSPFs) significantly increased R2 values.

The computational cost associated with uncertainty quantification of engineering problems featuring localized phenomenon can be reduced by confining the random variability of the model parameters within a region of interest.

The influence of all the other parameters in the variability of the model output is small.