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We have selected this solution because it seems the more coherent from a clinical point of view.
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A set of six clusters was selected, as this solution most clearly identified distinct and nutritionally meaningful dietary patterns while maintaining a reasonable sample size in each group for subsequent regression analyses.
A set of 6 clusters was selected, as this solution most clearly identified distinct and nutritionally meaningful dietary patterns while maintaining a reasonable sample size in each group for subsequent regression analyses.
To properly select this capacitor, several solutions have been proposed such as using Lagrange method, standard bacterial foraging and genetic algorithms.
According to Bent and Van Hentenryck [25], this selection should be performed using a consensus function to select the solution that is most similar to all other solutions.
Select the solution that makes the most sense for your application.
Then a decision-making tool (M-TOPSIS) selects the solution providing the best compromise.
The number of items removed from the solution is chosen randomly between 1% and 60% of the number of selected items in this solution.
The ruin quantity, i.e. the number of subsets removed from the solution, is a number chosen randomly between 1% and 60% of the number of selected subsets in this solution.
A way to characterize good solutions in such problems is to use the leximin preorder to compare the vectors of objective values, and to select the solutions which maximize this preorder.
In this study, we selected a solution system that the above two responses still remained almost constant.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com