Sentence examples for model that optimizes from inspiring English sources

Table 6 shows the profit advantage of the optimization model (that optimizes for (f_i) and (k_i)); the magnitude increases as order frequencies rise.

Accordingly, this paper presents the development, implementation, and validation of a new exterior panelized walls platform optimization (EPWPO) model that optimizes the tradeoff between minimizing the total fabrication cost of the panels and minimizing the resulting design deviation from enforcing common platform designs for the panels.

Besides, we propose a new mathematical programming model that optimizes both the network design and the allocation of security resources over the network.

Proposing a bi-objective model that optimizes both: (a) The exceptional and void elements, and;   (b) The total cost consisted of the fixed setup costs, the variable machine operation costs and the worker salary costs;     4.

Considering duplicate machines; Simultaneous grouping of workers, machines and parts into virtual cells; Proposing a bi-objective model that optimizes both: (a) The exceptional and void elements, and;   (b) The total cost consisted of the fixed setup costs, the variable machine operation costs and the worker salary costs;  .

We derive a model that optimizes the transmitted information and compare it directly with measurements of complete functional connectivity between cone photoreceptors and the four major types of ganglion cells in the primate retina, obtained at single-cell resolution.

The model that optimized the AIC score most frequently was the model with "preeclampsia" as the only contributing variable.

Professor Warren Powell is designing smart models that optimize the use of wind and solar power despite variability due to wind shifts and cloud cover.

To test these hypotheses, we used home range models that optimize resource use according to resource-maximizing and area-minimizing strategies to evaluate the home ranges of female black bears, Ursus americanus, living in the southern Appalachian Mountains.

In this work we apply statistical analysis of variance (ANOVA) and nonlinear least squares optimization with parameter estimation concepts, first, to assess the significance of the two factors and, second to formulate flow prediction models that optimize the feed rate and classification efficiency.

These include models that approximate proper Bayes' conditional dependence computations while requiring fewer training sample cases, attribute exclusion criteria between optimism and pessimism that improve accuracy, and ordering techniques for introducing attributes into Bayes models that optimize the information value associated with the attributes in test-sample cases.