I am trying to build a surrogate model with my experimental data. My computational model, which has 4 input parameters, has resonance-like results (which has an important issue in my computational model) (see figure 1).
I want to learn that how can I cover the resonance-like behavior with the surrogate model also. I mean, how my surrogate model should also exhibit resonance-like behavior?
Is your data coming from physical experiments (i.e. possibly having some noise), as opposed to computer simulations which would be free of noise? This could be a reason.
More generally, if your output is a (discretized) function of the frequency for each experiment, the resonances and anti-resonances are usually not aligned any more, which makes the direct computation of a surrogate for each frequency difficult. Techniques exist to solve this issue, see e.g.
My data is coming from computer simulations. In the beginning, the computation was done at 60 discrete points, later I increased this number to 1000 points (with the help of the continuous range option offered by the program).
Anyway, I will search for the techniques you mentioned.