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As an endeavor to robust optimization, the number of design variables to be simultaneously optimized is divided by grouping the scantling variables by the plane.
For the purpose of objective optimization, the number of FACTS, line load rate, line flow, and the loss of network are compared.
Unlike conventional optimization, the number of function evaluations in RDO is significantly more which often renders it time consuming and computationally cumbersome.
Since sigmodal gradients are much more complex than the traditional linear gradients and have a large number of input parameters (five) for optimization, the number of DOE experiments required for a full factorial design to estimate all the main effects as well as the interactions would be too large (243).
Without optimization, the number of new tests added to each testing program is independent of the cost ratio, although the distribution of resources does depend on the cost ratio.
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However, this is not the case for the LR test, which requires an additional factor I —the number of optimization steps used to fit the alternative model.
Kamrunnahar et al. [55] presented a systematic optimization algorithm for the optimization of the number and locations of electrodes in BCI systems adopting a wrapper approach with a complete search strategy for subset channel selection.
For the FPGA design, the reduction in the delay and power dissipation of the optimized DCT design with respect to those of the original DCT design reaches up to 15.2 % (9.0 %) and 9.7 % (10.2 %) obtained while targeting the optimization of the number of operations (the optimization of the number of operations under a delay constraint), respectively.
For the ASIC design, the reduction in the delay and power dissipation of the optimized DCT design with respect to those of the original DCT design reaches up to 17.3 % (17.4 %) and 37.4 % (39.4 %) obtained while targeting the optimization of the number of operations (the optimization of the number of operations under a delay constraint), respectively.
This optimization reduced the number of rules to 4097.
Figure 11 shows the speedup given by the optimization and the number of used CPU.
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