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Several criteria can be adopted for optimizing split-plot experimental designs: the most frequently used are D-optimality and I-optimality.
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The central Box Behnken design (BBD) and mathematical modelling were adopted for optimizing experimental parameters.
The total annual cost of MSHEN, obtained from the simulation of MSHEN according to the vertices of the polyhedral uncertain region, is regarded as an objective function, and GA/SA is adopted for optimizing the heat exchanger areas.
A two-factor, six-level factorial design was adopted for optimizing the flow rates of brine and catholyte in electrolyzed water generator in order to produce electrolyzed water (EW) having best decontamination performance for broccoli sprout washing.
In the determination of the suitable heat transfer temperature difference contribution values of the stream, the total annual cost of multistream heat exchanger network (MSHEN) is regarded as an objective function, and genetic/simulated annealing algorithm (GA/SA) is adopted for optimizing the heat transfer temperature difference contribution values of the stream.
Then, in order to avoid falling into local optimum, LSSVM optimized by MFOA is adopted for modeling.
Often, culture conditions optimized for roNSCs are adopted for use in hNSC culturing.
The evolution strategy is adopted in optimizing the geometry.
A particle swarm algorithm is adopted to optimize the weighting parameters for the sound pressure in the frequency domain so that simulated values approach the measured noise level.
Box Behnken design (BBD) and response surface methodology (RS M were adopted to optimize the synthesis condition for maximizing the photoluminescence quantum yield (PLQY).
The model of DFIG for small signal stability analysis was presented in [3] and the particle swarm optimization (PSO) method was adopted to optimize the controller parameters.
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