Sentence examples for modeling errors are from inspiring English sources

To reduce the errors, a third-order equation can be applied to the height model, and Fig. 7 shows that the modeling errors are reduced to ±0.05 mm.

Modeling errors are typically not homogenously distributed over the model, but are localized, e.g. in template-based models often in segments that had to be remodeled de novo.

On the other hand, when a fractional equation such as Eq. (14) is used, the modeling errors are similar to those of the third-order model as shown in Figs. 7 and 8, even though the number of coefficients is reduced.

Heteroscedasticity is a major concern in statistical modeling because it can invalidate statistical tests of significance which may assume that the modeling errors are uncorrelated and that the error variances do not vary with the effects being modeled.

The modeling errors are discussed for both sets of comparisons.

Conditions for robustness to modeling errors are derived by analyzing the norms of estimation errors.

An optimal residual generation with no modeling errors is used as the reference residual model of robust fault detection filter design for the uncertain discrete-time systems with both modeling errors and SNR constraints; then, the robust fault detection filter design is formulated as an optimal H∞ filtering problem.

Modeling errors were higher in areas where head model geometry differed most from the actual geometry of the head.

Having measurement and modeling errors is an inevitable part of data acquisition systems and finite element models.

The sensitivity of NDI to modeling errors is eliminated here by making use of a real time identified model of the aircraft.

Robustness to modeling errors is incorporated by choosing a distributed sensor network.