Sentence examples for implemented for the prediction from inspiring English sources

A new scheme was developed for assortment of the element risk factor (defined as the ratio of the strain energy density to the yield strain energy for each element) and implemented for the prediction of the failure strength.

Furthering our earlier work of indirect degradation estimation via a mixed time-/condition-based approach, a stage-based Gamma process is designed and implemented for the prediction of degradation PDF where a recursive Maximum Likelihood Estimation (MLE) algorithm deduced from the conventional MLE algorithm is able to update the modeling parameters based on each aperiodic monitoring interval.

Recently machine learning based approaches have been implemented for the prediction of ΔΔG in proteins upon residue substitution taking as input either the protein structure or sequence (for a recent review see [ 20]).

Two optimisation strategies, maximising the current density at a fix cell voltage and during a specific range, are implemented for the optima prediction.

Three mechanical-based techniques, including falling impact (FAI), forced impact (FOI), and acoustic impulse-response (AIR), were implemented for the nondestructive prediction of the apparent modulus of elasticity (Ea) and Magness-Taylor firmness (MTf) of kiwifruit, cv.

A full-physics 10-km resolution (10 km on the side) mesoscale model was implemented for the ensemble prediction of surface precipitation and temperature over the domain of Northern California with lead times out to 16 days with 6-hourly temporal resolution.

To the best of our knowledge, this concept has never been implemented for AMPs prediction and also for the other type of bioinformatics applications.

An analytically based and numerically implemented method for the prediction of the behavior of cable networks has been developed for the analysis of the in-plane free-vibration problem of a set of interconnected taut cable elements.

We implemented SVM for the prediction and classification of aaRSs because machine learning-based approaches were essential for the development of prediction tools.

Three methods, GBLUP, the original one-step blending and the adjusted one-step blending, were implemented for genomic prediction of animals in the validation population.

The end-to-end horizontally scalable application is designed and implemented for route prediction.