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Data-driven models with physical interpretability for real-time cavity profile prediction in electrochemical machining processes

Ming Wu, Zequan Yao, Mathias Verbeke, Peter Karsmakers, Benjamin Gorissen, Dominiek Reynaerts

2025Engineering Applications of Artificial Intelligence39 citationsDOIOpen Access PDF

Topics & Concepts

InterpretabilityComputer scienceMachiningData miningArtificial intelligenceMachine learningMechanical engineeringEngineeringAdvanced Machining and Optimization TechniquesAdvanced machining processes and optimizationHydrogen embrittlement and corrosion behaviors in metals
Data-driven models with physical interpretability for real-time cavity profile prediction in electrochemical machining processes | Litcius