Sentence examples for quantification of errors from inspiring English sources

Quantification of errors has also been used for numerical analysis of some central difference methods to solve this equation.

The fundamental strategy of verification is the identification and quantification of errors in the computational model and its solution.

Quantification of errors in face of the testing results was carried out for the most important parameters – ultimate load, strain and lateral stress – as well as for other curve parameters.

In addition calculation of the absolute deviation of algorithm counts from manual counts gives a more transparent quantification of errors.

The quantification of errors against possible pressure offsets within physiological limits will lead us to determine the feasibility of this second approach.

Characterization and quantification of errors in exposure estimates from these models will be available from validation studies (Nethery et al. 2008), and efforts should be made to also incorporate these in evaluations of congenital anomaly risk.

In this study, even though exact quantification of error is not given between the values of experimental and field observations, it was found that, for a particular density the corresponding flow values are slightly higher in experiments compared to field studies.

In this study, in which quantification of error is based on the variability between monitors, error due to spatial variation is much greater than error due to instrument imprecision, particularly for primary air pollutants [ 15].

These metrics also cannot be a quantification of measurement error, since measurement error simply propagates through the equation.

Systematic quantification of these errors has not yet been carried out, but in E. coli, under normal physiological conditions, average missense error is of the order of 10−3 to 10−4 [1], while frameshifting and nonsense errors may be one order of magnitude higher.

This paper describes a rigorous methodology for quantification of model errors in fungal growth models.