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Taken together, Figure 4, A and B, shows that under our model, smaller internal reference panels are more likely to be optimal than much larger external panels and that this improvement increases as the two source populations for the panels become more genetically distinct.
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And that makes optimal rates much lower than previously thought.Not everyone of working age contributes equally to supporting the dependent population.
As for 69 nodes system, it takes 6.22 times of average evolution generation and 0.534 s to find the optimal solution, much better than the results of [8].
With moderate process knowledge it is possible to design controllers that are much closer to optimal than the three tuning rules, with significant performance improvements as a result.
However, the two baseline policies in this scenario converge to the optimal much slower than in the uniform distributed scenario.
Lin and Kernighan also demonstrated that a 3-optimal solution is much better than a 2-optimal solution; however, a 4-optimal solution is not sufficiently superior to a 3-optimal solution to justify the additional computational cost.
These optimal values were much higher than those of mixed Cu–W composites.
Experimental results show that the performance of our optimal algorithm is much better than the performance of other existing optimal algorithms.
The experimental results show that with only five random starts we can achieve very similar performance of optimal one and much better than the existing approach.
Comparison between SGA and AGA: A comparison between the results from SGA and AGA shows that AGA was able to converge to optimal reservoir realizations much faster than the SGA.
The number N of points P i, equal to the number of points Q i of the optimal array, is much smaller than the number of points P k.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com