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We present an accurate modeling technique that exploits standard space mapping (SM) as a trend function and the correction layer implemented with kriging. The kriging process allows us to efficiently utilize all available fine model data (not possible in the standard SM approach) and to obtain accuracy better than both the SM and recently published combinations of SM and radial basis function interpolation...
We describe an improvement of a recent space mapping (SM) modeling approach that uses variable weight coefficients (SM‐VWC). Our modification alleviates the main drawback of SM‐VWC: the computational overhead related to a separate parameter extraction required for each evaluation of the surrogate model. In our new procedure, the output SM parameters of the surrogate model are obtained by solving a...
We review the latest developments in space‐mapping‐based modeling techniques with applications in microwave engineering. We discuss the two techniques that utilize a combination of standard space mapping and function approximation methodologies, in particular fuzzy systems and support vector regression (SVR). In both cases, the initial space‐mapping model is enhanced by an additional term that approximates...
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