Sentence examples for the output variability from inspiring English sources

In particular, sensitivity analysis can also be used for model calibration, model validation, decision making process, i.e. any process where it is crucial to identify which are the variables that mostly contribute to the output variability.

During peak flow (freshet) season, when power output is highest, the output variability is negligible.

However, if we increase intrinsic noise to much higher levels, as in Fig. 9c, this noise itself starts to contribute significantly to the output variability and the reliability of signal transmission is diminished again.

Numerical results show how the theory developed in this paper can be applied to analyse the dependency of the output variability and the service level on the system parameters.

We then discuss two simple examples that show how the theory developed in this paper can be applied to analyse the dependency of the output variability on the system parameters.

In this paper, an efficient methodology is proposed to analyze the output variability by a stochastic method based on fast Monte Carlo Simulation using a specific formulation obtained with the modal stability assumption.

Such issues must be solved to understand how the solar output variability may influence the Earth's environment (helioclimatology).

Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios.

Such energy has been skipped in many ways up to now in theoretical models describing the solar output variability.

A case study has been used to demonstrate the model output variability and to unravel whether or not more complex but also less manageable models offer a significant advantage to the designer.

The main idea of the proposed methodology is the utilization of experimental residence time distribution (RTD) measurements to (a) determine the contributions of feeding variability, powder segregation and RTD variability on output composition variance and (b) develop a predictive model of the output variance of a continuous mixer.