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Works matching IS 10954244 AND DT 2024 AND VI 27 AND IP 7

Results: 6

1

MTTLA‐DLW: Multi‐task TCN‐Bi‐LSTM transfer learning approach with dynamic loss weights based on feature correlations of the training samples for short‐term wind power prediction.

Published in:

Wind Energy, 2024, v. 27, n. 7, p. 733, doi. 10.1002/we.2909

By:

Song, Jifeng;
Peng, Xiaosheng;
Song, Jiajiong;
Yang, Zimin;
Wang, Bo;
Che, Jianfeng

Publication type:

Article

2

Wind‐assisted microgrid grid code compliance employing a hybrid Particle swarm optimization‐Artificial hummingbird algorithm optimizer‐tuned STATCOM.

Published in:

Wind Energy, 2024, v. 27, n. 7, p. 711, doi. 10.1002/we.2908

By:

Imtiaz, Saqif;
Yang, Lijun;
Azib Khan, Hafiz Muhammad;
Mudassir Munir, Hafiz;
Alharbi, Mohammed;
Jamil, Mohsin

Publication type:

Article

3

Analysing the cost impact of failure rates for the next generation of offshore wind turbines.

Published in:

Wind Energy, 2024, v. 27, n. 7, p. 695, doi. 10.1002/we.2907

By:

Donnelly, Orla;
Carroll, James;
Howland, Michael

Publication type:

Article

4

Multistep short‐term wind speed prediction with rank pooling and fast Fourier transformation.

Published in:

Wind Energy, 2024, v. 27, n. 7, p. 667, doi. 10.1002/we.2906

By:

Shu, Hailong;
Song, Weiwei;
Song, Zhen;
Guo, Huichuang;
Li, Chaoqun;
Wang, Yue

Publication type:

Article

5

Development and validation of a lifting‐line code associated with the vortex particle method software Dorothy.

Published in:

Wind Energy, 2024, v. 27, n. 7, p. 633, doi. 10.1002/we.2905

By:

Dufour, M.‐A.;
Pinon, G.;
Rivoalen, E.;
Blondel, F.;
Germain, G.

Publication type:

Article

6

Issue Information.

Published in:: Wind Energy, 2024, v. 27, n. 7, p. 629, doi. 10.1002/we.2834
Publication type:: Article