Limon Bin Hossain

A Deep Learning-Based Stacking Ensemble Framework for Turbofan Engine Remaining Useful Life Prediction

A two-level stacking ensemble framework for Remaining Useful Life prediction of turbofan engines, evaluated on the NASA C-MAPSS benchmark using the FD001 and FD003 subsets, demonstrates the efficacy of stacking ensemble methods for prognostics and health management in safety-critical aerospace applications.