Weber, TommyTommyWeberHillebrecht, TilTilHillebrechtSchuster, ChristianChristianSchuster2026-07-312026-07-312026-0630th IEEE Workshop on Signal and Power Integrity, SPI 2026https://hdl.handle.net/11420/64183Physics-based (PB) via models for printed circuit board (PCB) simulations are computationally efficient and have proven accurate up to 40 GHz. However, they require validation against time-intensive full-wave (FW) electromagnetic solvers when applied to faster links at 100 GHz. This study presents an error identification approach using a decision tree (DT) that categorizes designs into low- and high-error classes based on PCB design parameters, enabling targeted FW validation only where needed. The DT's interpretability reveals which geometric and material parameters most influence PB model accuracy.enDecision treesmachine learningmodel validationprinted circuit boards (PCBs)signal integrity (SI)Natural Sciences and Mathematics::537: Electricity and ElectronicsTechnology::600: TechnologyUsing decision trees for fast error identification in physics-based modeling of PCB structuresConference Paper10.1109/SPI68887.2026.11594791