Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects
S Liu, J Chen, Y Feng, Z **e, T Pan, J **e - Expert Systems with …, 2024 - Elsevier
Intelligent fault diagnosis, detection, and prognostics (DDP) for complex equipment
prognostics and health management (PHM) have achieved remarkable breakthroughs …
prognostics and health management (PHM) have achieved remarkable breakthroughs …
AugPlug: An Automated Data Augmentation Model to Enhance Online Building Load Forecasting
Online Building Load Forecasting (BLF) is a scheme that designs a model update strategy to
continuously update the deployed ML-based BLF model to adapt to changes in the …
continuously update the deployed ML-based BLF model to adapt to changes in the …
Improving Cyber-Physical Building Energy System via Large-Scale Machine Learning Evaluation
Y Deng - Proceedings of the 11th ACM International Conference …, 2024 - dl.acm.org
Machine learning (ML) is playing a crucial role in almost every business sector. In the
building automation sector, the Industries (eg, Siemens, Honeywell) depend on AI to …
building automation sector, the Industries (eg, Siemens, Honeywell) depend on AI to …
Spatial-Temporal Embodied Carbon Models for the Embodied Carbon Accounting of Computer Systems
Embodied carbon is the total amount of carbon released from the processes associated with
a product from cradle to gate. In many industry sectors, embodied carbon dominates the …
a product from cradle to gate. In many industry sectors, embodied carbon dominates the …
A Data-driven Framework for Occupant-centric Demand Flexibility Potential Evaluation at Scale
Z Yufei, D Yang, L Rui, L Yaohui, W Dan… - Proceedings of the 11th …, 2024 - dl.acm.org
Building demand flexibility is essential for balancing the grid as renewable energy
generation increases. However, the limited adoption of flexibility-enabling technologies …
generation increases. However, the limited adoption of flexibility-enabling technologies …