Abstract
This article presents a dual-mode Substrate Integrated Waveguide (SIW) filter by perturbing the square cavity for C band applications. The $$TE_{110}$$ and $$TE_{120}$$ perturbed modes are formed by introducing the center metallic via in the SIW square cavity, which has distinct field distributions. The proposed filter is designed by combining the solution of CST supported by Machine learning algorithms. The four regression algorithms (XGboost, random forest, decision tree, and K-Nearest Neighbor (KNN)) are compared and evaluated based on the accuracy score. Here KNN algorithm provides better accurate results of $$89\%$$ for $$S_{11}$$ and $$99.96\%$$ for $$S_{21}$$ . The RTduroid 5880 substrate is used for the fabricated filter of size 28.4 x 28.4 x 0.51 $$mm^3$$ . The fabricated and simulated SIW filter results are validated with slight discrepancies.
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