Xiu-Fei Li

A degradation-informed RUL prediction method for rolling bearings using RBSU-FI feature selection and a BiLSTM network

A novel degradation-informed RUL prediction method integrating robust symmetric uncertainty-feature importance (RBSU-FI) feature selection with a bidirectional long short-term memory network and a multi-layer perceptron compression module is proposed, outperforming representative feature selection methods and predictio...