Sentence examples for adaptation accuracy from inspiring English sources

Classical weighted mean (WM) method is a common statistic adaptation method because of its domain independent and easily to be implemented, but with lower adaptation accuracy.

Empirical comparison results indicated that AFCA achieves the better adaptation performance under k-NN than other SFCAs on the basis of the adaptation accuracy.

Statistical adaptation method is a classical method for feature-based case adaptation (FCA) because of its domain-independent and easily to be implemented, but with low adaptation accuracy.

Based on the parametric transformer design cases, the comparisons of adaptation performances between HWM and other statistical and intelligent methods were carried out, and the empirical results show that HWM has the better adaptation performance than other comparative methods by comparing the adaptation accuracy.

Through comparing the adaptation accuracies with those provided by other classical neuro-adaptation methods, the modularized adaptation is proved to be a feasible method for case adaptation.

Finally, for more usability of adaptation, sufficient accuracy of information and functionalities of application must be achieved.

The recording of auditory evoked potentials (AEPs) at fast rates allows the study of neural adaptation, improves accuracy in estimating hearing threshold and may help diagnosing certain pathologies.

Following adaptation, comparable accuracies were achieved in two ways: with visual feedback, adapted trajectories in force fields were straight whereas without it, they remained curved.

First, there is an adaptation speed-accuracy tradeoff conferred by network size (and to a lesser extent, recombination).

To summarize the results of this section, we show that prior force field adaptations influenced adapted trajectory but not accuracy during later adaptation to visuomotor rotations.

An underlying method for both engines, which is range accuracy adaptation, is presented.