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Moderately sized test sets show the smallest variability.
The raw materials were milled or chopped into four different sized test materials.
Computational experiments on real-world sized test instances demonstrate the efficiency and effectiveness of the proposed approach.
The proposed algorithms were empirically tested and compared by using various sets of differently sized test data: some theoretical classes of graphs with known optimal solutions and some special classes of graphs chosen from the literature for the k-minimum spanning tree and Roman domination problems.
Thus, the variability of the error estimates in the outer loop reached a minimum for moderately sized test sets.
Comparison has been carried out for larger sized test applications also, by implementing some of the prospective techniques.
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The pore sizes tested had no significant effect on tissue generation.
The plot in Fig. 6 shows the execution time and performance for the training set sizes tested.
When 15% PMME2000 was used as a precipitant, all the nanosphere sizes tested produced crystals.
MOO substantially improved the prediction of undirected networks, with all network sizes tested.
For all data set sizes tested, this difference is statistically significant.
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Justyna Jupowicz-Kozak
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