In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance

no code implementations • 25 Feb 2023 • Sotiris Pelekis, Evangelos Karakolis, Francisco Silva, Vasileios Schoinas, Spiros Mouzakitis, Georgios Kormpakis, Nuno Amaro, John Psarras

In power grids, short-term load forecasting (STLF) is crucial as it contributes to the optimization of their reliability, emissions, and costs, while it enables the participation of energy companies in the energy market.

Load Forecasting Out-of-Distribution Generalization +2

Perceptrons from Memristors

no code implementations • 13 Jul 2018 • Francisco Silva, Mikel Sanz, João Seixas, Enrique Solano, Yasser Omar

Memristors, resistors with memory whose outputs depend on the history of their inputs, have been used with success in neuromorphic architectures, particularly as synapses and non-volatile memories.