Enhancing wind speed forecasting accuracy using a GWO-nested CEEMDAN-CNN-BiLSTM model
This study introduces an advanced artificial model, grey wolf optimization (GWO)-nested complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-convolutional neural network (CNN)-bidirectional long short-term memory (BiLSTM), for wind speed forecasting. Initially, CEEMDAN with t...
Gorde:
| Egile Nagusiak: | , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Elsevier
2024-06-01
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| Saila: | ICT Express |
| Gaiak: | |
| Sarrera elektronikoa: | http://www.sciencedirect.com/science/article/pii/S2405959523001522 |
| Etiketak: |
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