Automated　model　generation　(AMG)　is　recognized　as　an　efficient　method　to　automatically　develop　artificial　neural　network　(ANN)　models　for　microwave　components.　It　replaces　the　complicated　manual　operations　during　ANN　modeling　with　a　completely　automated　ANN　development　framework,　thus　effectively　improving　the　ANN　modeling　efficiency.　In　this　paper,　a　recent　advanced　AMG　method　combining　interpolation　techniques　and　multilayer　neural　model　structure　adaptation　is　presented　and　a　microwave　cavity　filter　modeling　example　is　used　to　demonstrate　the　effectiveness　of　presented　method.　©　2023　Applied　Computational　Electromagnetics　Society　(ACES).