Sentence examples for predictive uncertainty of the model from inspiring English sources

If spatially highly resolved precipitation was used during model parameter estimation, the predictive uncertainty of the model was clearly reduced.

We will demonstrate that the goals of traditional experiments and validation experiments are often in conflict, making use of traditional experimental results problematic and leading directly to larger predictive uncertainty of the CFD model.

Quantification of the predictive uncertainty of subsurface models has long been investigated.

The hypothesis is that including HOF metrics derived from the performance shaping factors (PSFs) influencing maintenance tasks can reduce the predictive uncertainty of models developed for system failure probability estimation, provided that the PSFs are found to be significant predictors of the failure event.

Inclusion of significant HOF metrics derived from performance shaping factors (PSFs) should reduce the predictive uncertainty of models developed for system failure probability estimation.

The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment.

The predictive uncertainty of future streamflow is estimated through the Bayesian integration of two separate processors.

During the past decades much progress has been made in the development of computer based methods for parameter and predictive uncertainty estimation of hydrologic models.

The response surface designs hold an assumption of pre-definition of the model structure, which may introduce uncertainty in the predictive ability of the model.

These sensitivities are used to rank the importance of parameters in contributing to response uncertainties, and also serve within the predictive methodology as the weighting functions for propagating uncertainties of the model parameters and for assimilating measurements and simulations.

The procedure first performed two-stage Monte-Carlo simulations to ensure predictive accuracy by obtaining behavior parameter sets, and then the estimation of CV-values of the model outcomes, which represent the predictive uncertainties for a model structure of interest with its associated behavior parameter sets.