Forecasting high-frequency spatio-temporal wind power with dimensionally reduced echo state networks

DOI10.1111/rssc.12540MaRDI QIDQ6643933

Marc G. Genton, Stefano Castruccio, Huang Huang

Publication date: 27 November 2024

Published in: Journal of the Royal Statistical Society. Series C. Applied Statistics (Search for Journal in Brave)

zbMATH Keywords

machine learningspace-time modelGaussian random fieldecho state networkreservoir computing

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items (1)

Calibrated forecasts of quasi-periodic climate processes with deep echo state networks and penalized quantile regression

This page was built for publication: Forecasting high-frequency spatio-temporal wind power with dimensionally reduced echo state networks