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According to response optimizer, the optimal moisture level was 30% for all bioremediation processes.
In the software response optimizer tool determined the optimal value for maximum antimicrobial activity.
A numerical optimization was carried out using response optimizer function in the Minitab software for simultaneous optimization and to determine the exact optimum levels of these variables (x 1, x 2, x 3 and x 4 ) leading to the desired equilibrium headspace concentration of soursop flavor compounds.
With the help of response optimizer, we have found the optimal parameter setting for all three responses: Response Goal Lower Target Upper Weight Importance GRG Maximum 0.3661 1 1 1 1.
Moreover optimization was done using response optimizer part of Minitab software and the values of target and allowable minimum responses were defined for the software and finally it calculated the maximum achievable values for both of the responses and also corresponding coded values of mixture components.
The response optimizer was employed to generate the optimal set of four factors leading to the desired criteria of response variable.
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The process conditions were optimized using Response Surface Optimizer Tool in MINITAB 16 and pH = 3.5 and H2O2 concentration of 8.5 g/L was obtained as optimum condition leading to 49.39 ± 0.93% CBZ removal from pharmaceutical wastewater containing higher CBZ concentrations.
Since orbit dynamics models and finite element structural model are computationally expensive, an adaptive response surface surrogate based optimizer is incorporated in the proposed framework to solve the satellite MDO problem with moderate computational cost, where a response surface surrogate is gradually refined to represent the computationally expensive MDA process.
Finally, another tool "Reaction knock-out optimizer" deletes the pairs sequentially and optimizes the objective function.
Thanks to the performance of the proposed hybrid optimizer, frequency-response performances of the redesigned digital system using the digital controller evolutionarily derived by the proposed approach bare a far better resemblance to its continuous-time counter part in comparison to those obtained using existing open-loop discretization methods.
Responsibility for building the optimizer was handed off to Wagner.
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