Nature

Hybrid Gaussian process regression with temporal feature extraction for partially interpretable remaining useful life interval prediction in Aeroengine prognostics

The estimation of Remaining Useful Life (RUL) plays a pivotal role in intelligent manufacturing systems and Industry 4.0 technologies. While recent advancements have improved RUL prediction, many ...
Nature

Gaussian process regression with physics-guided pseudo-sample augmentation for wear prediction under sparse measurements in milling

Tool wear prediction is essential to ensure machining quality and sustainability. Hybrid physics-data Gaussian process regression (GPR) methods integrate domain knowledge with data-driven learning, ...