Sentence examples for optimization terms from inspiring English sources

Adding extra optimization terms for other neighboring cells only brings minimal performance at a high-complexity cost since most of the per-subcarrier interference comes from one base station[23].

Using a finite element model of the structure to calculate the dynamic behaviour analytically, it is possible to formulate the inverse problem in optimization terms and then to utilize a solution procedure employing genetic algorithms.

Although the CG force field is built at one single thermodynamic state point without any temperature correction or pressure optimization terms, the CG model possesses a rather favorable transferability in a wide temperature of 100 600 K.

In optimization terms, each individual in the population is encoded into a string or chromosome that represents a possible solution to a given problem.

Here we describe a new in silico automatic tool for structure-based lead optimization, termed LEADOPT.

An optimization term is introduced from the perspective of the tire grip margin to construct a stability objective function.

However NMSE(I, I d ) only focuses on the global similarity, so SSIM I, I d ) is introduced as an optimization term to evaluate the local structure similarity between the dithering pattern and the corresponding ideal pattern.

The author compared the performance of ABC with the performance of genetic algorithm and particle swarm optimization in terms of fitness convergence characteristic, optimal fitness, and computation time.

Based on the monotonicity analysis, two efficient algorithms are then formulated to solve the suggested RIA-based and PMA-based hybrid reliability models, in which the outer-layer optimization in terms of random variables and the inner-layer optimization in terms of interval parameters are executed by turns.

Users can manage product listings, inventory availability, pricing optimization, search terms, data analytics and other critical functions across sites.

Generally, optimization in terms of the number of objective functions and optimization criteria is divided into two categories of single-objective optimization problems and multi-objective optimization problems.