Sentence examples for predictions with standard from inspiring English sources

Calibration results in a 2 3-fold reduction in the mean relative error for predicted pressure gradient/liquid holdup, relative to predictions with "standard" Ergun coefficients, when an idealized set of momentum equations are solved.

The data are found to be in good agreement with the theoretical predictions with standard deviations of less than 10% for most of the average torque and flow rate data points.

Using reflectance data, our VisNIR penetrometer yielded quantitative SOC predictions with standard error of prediction (SEP = 0.19 log[g kg−1]) and ratio of prediction to determination (RPD = 2.34) highly similar to the ASD contact probe (SEP = 0.18 and RPD = 2.45).

However, Sun and Mashima [29] correlation gives the best predictions with standard deviation of 13% for high mass flux only, but it over predicts measurements for low mass fluxes.

Permits to discharge are determined by comparison of design predictions with standards.

The model proposed by Fafitis & Shah 1985 can make a more accurate prediction with standard deviation 3.92% and 21.88% in peak stress and strain, respectively, compared to predictions made by other models.

Motivation: The repetitive nature of plant disease resistance genes encoding for nucleotide-binding leucine-rich repeat (NLR) proteins hampers their prediction with standard gene annotation software.

Furthermore, it shows that the addition of arterial stiffness improved cardiovascular risk stratification in relation to a prediction model with standard risk markers and that its predictive power is higher in younger individuals and patients with microvascular complications and poor glycemic control.

As the complexity of catalyst structures increases, new features will be needed to learn underlying correlations and avoid introducing significant errors on top of the average DFT prediction errors expected with standard semi-local generalized gradient approximation (GGA) functionals.

From these we draw two conclusions: in most cases divergence features slightly improve prediction when combined with standard features and in general computing standard features on the N-terminal 20 residues leads to higher accuracy than computing on 40 residues.

It would also be useful to compare the accuracy and cost efficacy of predictions from LiDAR data with standard inventory methods for the scheduling of production thinning operations and later more detailed inventories in stands of Douglas-fir.