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The performance under the multi-objective optimization is compared with those of single-objective optimization methods in terms of power, efficiency, and ECOP.
Finally, the LSER approach for the selectivity optimization is compared with a statistical response surface methodology (RS M based on a central composite design (CCD) in terms of the effectiveness and number of experiments.
Lattice constant of bulk In0.53Ga0.47As after geometry optimization is compared with the theoretical one based on the Vigard law, which proves the reliability of the parameters of the geometry optimization.
In other words, the relative gain in (19) tells us how much more energy-efficient LD power optimization is compared to classical TP minimization.
The optimization is compared for a number of well-known sets of multiple windows and common weighting factors and the results show that the number and the shape of the windows are important for a small mean square error.
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The quenching results after optimization are compared with those before optimization.
Finally, the results of optimization before and after optimization are compared by the test bench.
Results of exergoeconomic optimization are compared with corresponding features of the base case system.
Then, the aniline removal efficiency of LSCFB pre and post optimization was compared.
The results of three-objective optimization are compared with two different combinations of two-objective problems.
The results obtained by GA optimization are compared to those obtained by analytical methods.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com