Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …
The frequency and intensity of extremes and other associated events are continuously …
[HTML][HTML] A review on rainfall forecasting using ensemble learning techniques
S Kundu, SK Biswas, D Tripathi, R Karmakar… - e-Prime-Advances in …, 2023 - Elsevier
Significant challenges to human health and life have arisen as a result of heavy rains.
Floods and other natural disasters that affect people all over the world every year are …
Floods and other natural disasters that affect people all over the world every year are …
A hierarchical classification/regression algorithm for improving extreme wind speed events prediction
A novel method for prediction of the extreme wind speed events based on a Hierarchical
Classification/Regression (HCR) approach is proposed. The idea is to improve the …
Classification/Regression (HCR) approach is proposed. The idea is to improve the …
Analysis, characterization, prediction and attribution of extreme atmospheric events with machine learning: a review
Atmospheric Extreme Events (EEs) cause severe damages to human societies and
ecosystems. The frequency and intensity of EEs and other associated events are increasing …
ecosystems. The frequency and intensity of EEs and other associated events are increasing …
Improving the prediction of extreme wind speed events with generative data augmentation techniques
M Vega-Bayo, J Pérez-Aracil, L Prieto-Godino… - Renewable Energy, 2024 - Elsevier
Abstract Extreme Wind Speed events (EWS) are responsible for the worst damages caused
by wind in wind farms. An accurate estimation of the frequency and intensity of EWS is …
by wind in wind farms. An accurate estimation of the frequency and intensity of EWS is …
[HTML][HTML] Interpretable extreme wind speed prediction with concept bottleneck models
C Álvarez-Rodríguez, E Parrado-Hernández… - Renewable Energy, 2024 - Elsevier
Abstract Concept-bottleneck models (CBMs) are a new paradigm to construct interpretable
classifiers. The CBM architecture can be regarded as a neural network with a single hidden …
classifiers. The CBM architecture can be regarded as a neural network with a single hidden …
[图书][B] Optimization-based energy management for multi-energy maritime grids
This open access book discusses the energy management for the multi-energy maritime
grid, which is the local energy network installed in harbors, ports, ships, ferries, or vessels …
grid, which is the local energy network installed in harbors, ports, ships, ferries, or vessels …
Historical winter storm atlas for Germany (GeWiSA)
C Jung, D Schindler - Atmosphere, 2019 - mdpi.com
Long-term gust speed (GS) measurements were used to develop a winter storm atlas of the
98 most severe winter storms in Germany in the period 1981–2018 (GeWiSa). The 25 m× 25 …
98 most severe winter storms in Germany in the period 1981–2018 (GeWiSa). The 25 m× 25 …
Current gust forecasting techniques, developments and challenges
P Sheridan - Advances in Science and Research, 2018 - asr.copernicus.org
Gusts represent the component of wind most likely to be associated with serious hazards
and structural damage, representing short-lived extremes within the spectrum of wind …
and structural damage, representing short-lived extremes within the spectrum of wind …
Neural fuzzy inference system-based weather prediction model and its precipitation predicting experiment
J Lu, S Xue, X Zhang, S Zhang, W Lu - Atmosphere, 2014 - mdpi.com
We propose a weather prediction model in this article based on neural network and fuzzy
inference system (NFIS-WPM), and then apply it to predict daily fuzzy precipitation given …
inference system (NFIS-WPM), and then apply it to predict daily fuzzy precipitation given …