In this paper, a computational intelligence method to model lossy substrate integrated waveguide (SIW) cavity resonators, the Neural Network Residual Kriging (NNRK) approach, is presented. Numerical results for the fundamental resonant frequency f r and related quality factor Q r computed for the case of lossy hexagonal SIW resonators demonstrate the NNRK superior estimation accuracy compared to that provided by the conventional Artificial Neural Networks (ANNs) models for these devices.

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