Sentence examples for optimization setting from inspiring English sources

Since the hole distribution problem can be formulated as a topology optimization problem, the eigenfrequencies of the double cavity system having a partition with holes can be controlled by an optimal multi-hole distribution solved in the topology optimization setting.

Such an outcome suggests that the current methods need improvement to capture the overall physics of the binding phenomenon for consistent applications in a lead optimization setting.

Numerical simulations of the three cases of c demonstrate that better overall performance can be achieved with more design parameters in the multi-objective optimization setting.

DUA serves as an extension to current NUM theory in order to mainly treat and overcome issues that arise from the use of static utilities, when aiming at introducing users' short-term goals or prerequisites under a NUM optimization setting.

Examples from the multiobjective optimization literature are presented to show that the proposed procedure can improve substantially previously proposed statistical improvement criteria for the computationally intensive multiobjective optimization setting.

The two levels of this single-act hierarchical optimization setting together comprise a pair of objective functions, namely, (F : mathbb {R}^{u} times mathbb {R}^{l} rightarrow mathbb {R}) and (f : mathbb {R}^{u} times mathbb {R}^{l} rightarrow mathbb {R}) [7, 26, 28, 29].

However, if a large amount of compounds with a considerably different scaffold is present in the optimization set, the optimized weights might not completely coincide with the binding mode of the optimized query.

Systematic design and optimization set the standard in today's petrochemical industries, but their impact is limited when considering most proceses in metallurgical industries.

To verify whether our model actually has any predictive power, we also checked how the model behaves when it is applied to elongations that were not part of the optimization set.

Rather than excluding individual saccadic elongations or constant-speed stretches from the optimization set, as is usually done in cross-validation, we tested the model on two completely different paradigms: sequences of two step-wise elongations (0.5 mm each), and sequences of two saccadic elongations (1.6 mm each).

The distribution of the weights critically depends on the ligands in the optimization set.