S. Harisha

Explainable Machine Learning with Optimized Tree-Based Models and Statistical Validation for Data-Driven Wear Prediction of Carburized and Non-Carburized Engineering Steels

Accurate prediction of wear behavior in steel materials is essential for enhancing component durability and optimizing manufacturing processes. This study presents a comparative data-driven framework for wear prediction using Decision Tree (DT), Random Forest (RF), and a Physics-Informed Neural Network (PINN). Hyperpar...