Sentence examples for models with strong from inspiring English sources
Quantum simulators first and foremost offer a promising alternative when analytical and numerical methods fail in analysing models with strong correlations.
The new method is contrasted with other alternatives and shown to provide robust models with strong predictive components across all latent variables.
Such peculiarities indicate the unacceptability of weak field approximation for FeI 5233 line and need interpretation in the framework of inhomogeneous models with strong magnetic field components.
However, strong similarities exist between models (members of an ensemble) which may cause biased climate response toward models with strong similarities.
Our approach yielded parsimonious models with strong predictive capability for Vcmax (at 30 °C) and EV (R2 of withheld data = 0.94 and 0.92, respectively), both of which varied substantially in the field (≥ 1.7 fold) across the sampled crop types.
Under the dependence assumption of the errors, Berlinet et al. [6] proved the consistency of M-estimates for linear models with strong mixing errors.
One concrete result of the recommendations is the 'model farm' plan with a strong link between investment in production, investment in equipment and management for environmental purposes.
Grossman argues for lower government barriers to disruptive business models, with stronger commitments from companies to provide data to fuel regulations informed by these companies' actual impact.
To conclude, adaptive Gaussian quadrature is a relevant alternative for the evaluation of MF for models with stronger nonlinearity, while being more computationally efficient than standard quadrature.
Dynamo models with stronger magnetic advection effects exhibit more distortion from the outer boundary to depth.
In addition, models with stronger LTM in the current climate tend to show larger increase in LTM in a warming climate, leading to an LTM control for change in the intensity of convective BL dehydration and resultant cloud feedback.
