Sentence examples for condition uncertainty from inspiring English sources

Dynamical propagation of parametric and initial condition uncertainty is studied.

If the initial condition uncertainty obeys a symmetry condition, the new definitions are found to reduce to the original definition of participation factors.

Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function.

In this respect the understanding of numerical error, the sensitivity of the solution to parameters associated with input data, boundary condition uncertainty, and mathematical models is critical.

In order to manage all three sources of uncertainty, this study combines ESP with ensemble data assimilation, to quantify initial condition uncertainty, and Sequential Bayesian Combination, to quantify model errors.

There are many approaches to improve hydrologic model predictions, including pre-processing to deal with input uncertainty, data assimilation to treat initial and boundary condition uncertainty, model calibration to reduce parametric uncertainty.

Therefore, the mathematic procedure of dynamic UP via both methods considering parametric and initial condition uncertainties are comparatively discussed and studied in the present paper.

The equation the space industry typically uses to estimate Ec is presented, along with its sensitivity to typical assumptions, models, and initial condition uncertainties.

The propagation of initial conditions uncertainties is evaluated in terms of mean and variance of several thermodynamic properties of the two phases.

There are several sources of uncertainty in chemical metrology like sampling, environmental conditions, uncertainties of masses, volumes, equipment, reference values, measuring equipment approximation, assumptions incorporated in experimental methods, random variations, etc.

There are several sources of uncertainty in chemical metrology like incomplete definition, sampling, environmental conditions, uncertainties of masses, volumes, equipment, reference values, measuring equipment approximation, assumptions incorporated in experimental methods, random variations, etc.