Conference
Open access
2026
An Attention-Based TabNet Framework for Fault Detection and Diagnosis in HVAC Systems with Limited Labeled Data
An enhanced TabNet-based semi-supervised framework for multi-class HVAC fault detection, incorporating rigorous pseudo-label generation via Label Propagation, cost-sensitive learning for imbalanced classes, and hybrid feature engineering is introduced.
I. Samuel, B. Stephen, S. Ozuomba et al.
· E3S Web of Conferences · 0 citations