Bayesian approach to design optimization of electromagnetic systems under uncertainty
František Mach · 2016
Bayesian optimization approach to electromagnetic design under uncertainty is addressed. Latin hypercube sampling is used as experimental design criterion for initial set of samples. This set of training samples is used in order to build a suitable surrogate model and also to estimate observed noise variance strongly affecting simulation and optimization results, especially in the case of stochastic objective functions.