Author

H. Allasi

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Open access Oct 2026

Physics-informed sparse deep neural networks for ultra-fast solar power forecasting and frequency response support in ancillary service markets

The results show the potential of physics-informed sparse learning as a disruptive tool for reliable, scalable and commercially viable participation of solar in fast frequency response services, thus increasing the resilience and sustainability of future low-carbon power systems.

Asit Mohanty, A. Ramasamy, S. Mohanty et al. · Scientific Reports · 0 citations

#federated learning Open access Sep 2026

A privacy preserving federated meta ensemble stacking framework with explainability and differential privacy for chronic kidney disease prediction in resource constrained settings

Findings demonstrate that the proposed framework provides an accurate, privacy-aware, and interpretable solution for decentralized CKD prediction, and maintains robust performance under Gaussian noise.

Komal Kumar Napa, D. Sathyanarayanan, Raguraman Purushothaman et al. · Discover Artificial Intellig... · 0 citations