Short-term wind speed prediction based on temporal convolutional networks DOI

Sicheng Fan

2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Journal Year: 2023, Volume and Issue: unknown, P. 165 - 169

Published: Dec. 8, 2023

To improve the utilization efficiency of wind energy, this research proposes a hybrid model based on Temporal Convolutional Network (TCN) and two-level speed decomposition. Firstly, original data is decomposed into main residual signals through Singular Spectrum Analysis (SSA). Then, usage Variational mode decomposition (VMD) decomposes several sub-sequences. The next step involves predicting signal all sub-sequences using TCN. Eventually, Grey Wolf Optimizer (GWO) employed to perform optimization stack prediction results, resulting in outcomes. results demonstrate that proposed SSA-VMD-TCN-GWO outperforms reference models. Thus, provides new solution

Language: Английский

Optimal operational analysis of metamodel based single mixed refrigerant cryogenic process for floating liquefied natural gas plant technology DOI
Wahid Ali

Results in Engineering, Journal Year: 2022, Volume and Issue: 16, P. 100744 - 100744

Published: Oct. 31, 2022

Language: Английский

Citations

1
Short-term wind speed prediction based on temporal convolutional networks DOI

Sicheng Fan

2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Journal Year: 2023, Volume and Issue: unknown, P. 165 - 169

Published: Dec. 8, 2023

To improve the utilization efficiency of wind energy, this research proposes a hybrid model based on Temporal Convolutional Network (TCN) and two-level speed decomposition. Firstly, original data is decomposed into main residual signals through Singular Spectrum Analysis (SSA). Then, usage Variational mode decomposition (VMD) decomposes several sub-sequences. The next step involves predicting signal all sub-sequences using TCN. Eventually, Grey Wolf Optimizer (GWO) employed to perform optimization stack prediction results, resulting in outcomes. results demonstrate that proposed SSA-VMD-TCN-GWO outperforms reference models. Thus, provides new solution

Language: Английский

Citations

0