Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-022-24641-x.pdf
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3. Artin J, Valizadeh A, Ahmadi M, Kumar SA, Sharifi A (2021) Presentation of a novel method for prediction of traffic with climate condition based on ensemble learning of neural architecture search (NAS) and linear regression. Complexity, 2021
4. Awosusi AA, Xulu NG, Ahmadi M, Rjoub H, Altuntaş M, Uhunamure SE, Akadiri SS, Kirikkaleli D (2022) The sustainable environment in Uruguay: the roles of financial development, natural resources, and trade globalization. Front Environ Sci 10:875577
5. Barenya B H, Deepak G, Narayanan N (2022) Wavelet kernel least square twin support vector regression for wind speed prediction. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-18655-8
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1. A hybrid methodology using VMD and disentangled features for wind speed forecasting;Energy;2024-02
2. Forecasting model for short-term wind speed using robust local mean decomposition, deep neural networks, intelligent algorithm, and error correction;Frontiers in Energy Research;2024-01-25
3. VMD-SCINet: a hybrid model for improved wind speed forecasting;Earth Science Informatics;2023-11-30
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