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The proposed procedure which included optimization and sensitivity analysis was implemented to optimize the design parameters of the column and obtain the sensitive variables simultaneously, without requirement to run various simulations.
A Doehlert design was implemented to optimize this process.
Taguchi method based on three levels, six variables L27 orthogonal array robust design was implemented to optimize experimental conditions.
Principal component analysis and Box Behnken experimental design was implemented to optimize the agglomerates with good micromeritics and mechanical properties.
Then, a central composite design (CCD) was implemented to optimize both the separation and the detection of plasticizers.
In order to improve the machining performance, the Box Behnken method was implemented to optimize the parameters.
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The Kriging surrogate modeling technique and multiobjective particle swarm optimization (MOPSO) algorithm were implemented to optimize the FGF-filled bumper beam.
Secondly, a multi-objective particle swarm optimization (MOPSO) algorithm is implemented to optimize the DSMC parameters in order to decrease the normalized angle error of the pole and normalized distance error of the cart, simultaneously.
The design approach is implemented to optimize a real design mold and the final optimal design is prototyped in SLA and the manufacturability in PBF has been discussed.
One simple technique has been implemented to optimize the display of larger molecules.
Then, what strategies are implemented to optimize the cost function at the minimal cost?
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