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In summary, the multiple response surface optimization result of this study was desirable.
The mathematical model of ANN-MRSM is established by using artificial neural network to fit the multiple response surface function.
Multiple response surface optimization has attracted a great attention, while, the research about optimizing three or more responses employing response surface methodology (RSM) was very few.
A set of nondestructive data have been gathered based on general factorial design of experiments and used for training and testing the multiple response surface model.
As demonstrated in the comparison of methods (Monte Carlo (MC) method, traditional response surface method (RS M, multiple response surface method (MRS M and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy.
To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method (AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability.
Similar(53)
To overcome this issue, an improved multiple response surfaces method is proposed.
This study proposes a method for optimally balancing various affective satisfaction dimensions based on the multiple response surfaces (MRS) methodology.
The preparation parameters were optimized by using Box Behnken design and Multiple-response surface methodology with desirability function.
However, little attention has been given to the multiobjective optimization of correlated multiple responses using response surface with combined arrays.
The multiple regression and response surface analyses indicated that the interaction between C/N and C/Mg had the utmost effect on the reduction of surface tension and biosurfactant production.
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