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The response surface methodology was used for the experiment optimization.
A numerical simulation project was designed by an orthogonal experiment optimization design method.
using a central composite design (CCD), which is a response surface methodology (RS M, was used for the model fitting and experiment optimization of response parameters.
As a result of verification experiment, optimization made by reducing (to about 89%) test number with help of Taguchi was achieved within 95% confidence interval.
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Using the results of factorial experiments, optimization experiments were carried out by response surface methodology.
DOE consists of four primary classes of experimental designs: factorial experiments, factor-screening experiments, optimization experiments and mixture experiments.
DI was responsible for all aspects of performance of the experiments, optimization of the primers used, senior technical aspects, caspase assays and manuscript preparation.
Applying the results from central composite design (CCD) experiments, further optimization experiments were carried out using response surface methodology (RS M.
In this experiment, the optimization of the preparation parameters was carried out with the help of Response Surface Methodology.
Thus, sodium gluconate was chosen to be tested for the simultaneous PHAs and RLs production in the experiment for optimization of phosphate concentration.
The experiment design, optimization, and the 3D response surface plot were accomplished using the Design-Expert software, version 8.0.7.1 (Stat-Ease, Inc., USA).
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