A wind speed forcasting model based on rime optimization based VMD and multi-headed self-attention-LSTM

W Liu, Y Bai, X Yue, R Wang, Q Song - Energy, 2024 - Elsevier
Due to the nonlinearity, fluctuation, and intermittency of wind speed, its accurate prediction is
essential for improving efficiency in wind power operation systems. In this regard, a hybrid …

Hybrid AI-enhanced lightning flash prediction in the medium-range forecast horizon

M Cavaiola, F Cassola, D Sacchetti, F Ferrari… - Nature …, 2024 - nature.com
Traditional fully-deterministic algorithms, which rely on physical equations and mathematical
models, are the backbone of many scientific disciplines for decades. These algorithms are …

[HTML][HTML] Calibrating the CAMS European multi-model air quality forecasts for regional air pollution monitoring

G Casciaro, M Cavaiola, A Mazzino - Atmospheric environment, 2022 - Elsevier
The CAMS air quality multi-model forecasts have been assessed and calibrated for PM 10,
PM 2.5, O 3, NO 2, and CO against observations collected by the Regional Monitoring …

The added value of high-resolution downscaling of the ECMWF-EPS for extreme precipitation forecasting

PE Tuju, F Ferrari, G Casciaro, A Mazzino - Atmospheric Research, 2022 - Elsevier
We have considered the most severe flood events that affected Liguria region (northwestern
Italy) in the last decade, between October 2010 and October 2019. High-resolution …

Wind Power Forecasting in a Semi-Arid Region Based on Machine Learning Error Correction

MLS Araujo, YKL Kitagawa, ALC Weyll, FJL Lima… - Wind, 2023 - mdpi.com
Wind power forecasting is pivotal in promoting a stable and sustainable grid operation by
estimating future power outputs from past meteorological and turbine data. The inherent …