Although diagnostic questions were included in the methods, the responses to these are not analysed here.
In structural reliability analysis where the structural response is computed from the finite element method, the response surface method is frequently used.
In the impedance method, the response characteristics of the electrical signal heavily depend upon flow pattern, as well as phasic volume.
In the proposed method, the response of a HUSAS is approximated as a linear function of random variables using the stochastic perturbation analysis.
For the development of the method, the Response Surface Methodology was used, based on a Box Wilson Central Composite experimental design.
An estimation of the model parameters is performed using three methods: the design of experiments (DoE) method, the response surface method (RS M and the multiple linear regression (MLR) method.
Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN).
In each iteration of the method, the response coefficients are calculated using a unit rate added to the current managed flow rates; the current managed rates are derived from the previous iteration's optimal withdrawal rates.
In this method, the response variable (primary outcome) is depression (yes, no).
By using a smaller damping constant in the DLS method, the response speed can be improved, sacrificing some stability.
