3 papers
eess.SP2026
Boosted Enhanced Quantile Regression Neural Networks with Spatiotemporal Permutation Entropy for Complex System Prognostics
David J Poland
This paper presents an integrative prognostic framework that combines Spatiotemporal Permutation Entropy (STPE), Boosted Enhanced Quantile Regression Neural Networks (B-EQRNNs), Ga…
cs.RO2025
Enhanced Quantile Regression with Spiking Neural Networks for Long-Term System Health Prognostics
David J Poland
This paper presents a novel predictive maintenance framework centered on Enhanced Quantile Regression Neural Networks EQRNNs, for anticipating system failures in industrial robotic…
eess.SP2024
Industrial Machines Health Prognosis using a Transformer-based Framework
David J Poland, Lemuel Puglisi, Daniele Ravi
This article introduces Transformer Quantile Regression Neural Networks (TQRNNs), a novel data-driven solution for real-time machine failure prediction in manufacturing contexts. O…