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The figures of merit used for evaluation and comparison were acquired in the optimal conditions for each modifier, established by multivariate optimization of the main variables based on Doehlert designs.
Experimental designs were applied for multivariate optimization of the experimental conditions of RP-HPLC method.
A response surface methodology (RSM) based on central composite chemometrics design was used for multivariate optimization of the effects of three different parameters influencing the extraction efficiency.
Developing a robust, intelligent design tool for multivariate optimization of multi-phase transport in fuel cell diffusion media (DM) is of utmost importance to develop advanced DM materials.
In order to improve the chromatographic resolution (Rs) with an acceptable total analysis time, experimental designs for multivariate optimization of the experimental conditions were applied.
The multivariate optimization of the experimental conditions was carried out by means of the response surface study, considering as responses the resolution values and analysis time.
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The utility of multivariate optimization methods in the determination of aqueous photolysis rates of organic compounds is examined in this study.
By using any multivariate optimization algorithm, the set of hyperparameters θ can be estimated analytically.
The main difference between this method and the classical methods of multivariate optimization (weighted sum, goal programming, and goal attainment) is the reaction in finding the answers to different objectives [24].
The influence of various parameters affecting the CZE separation (buffer pH and concentration, acetonitrile percentage, capillary temperature and applied voltage) was investigated by means of multivariate optimization using experimental designs so as to obtain the highest efficiency.
These variables were accurately optimized using multivariate optimization strategies.
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