Interpretable wind speed forecasting through two-stage decomposition with comprehensive relative importance analysis DOI
Huanze Zeng, Binrong Wu, Haoyu Fang

et al.

Applied Energy, Journal Year: 2025, Volume and Issue: 392, P. 126015 - 126015

Published: May 5, 2025

Language: Английский

Constrained Deep Reinforcement Transfer Learning for Short-Term Forecasting of Wind Discrepancies at Ocean Stations DOI
Jun Zhang, Yaoran Chen,

Hang Pan

et al.

Neurocomputing, Journal Year: 2025, Volume and Issue: unknown, P. 129491 - 129491

Published: Jan. 1, 2025

Language: Английский

Citations

2
Prediction of Electricity Consumption in Residential Areas using Temporal Fusion Transformer and Convolutional Neural Network DOI

B. N. Shwetha,

Harish Nandhan S

Journal of Machine and Computing, Journal Year: 2025, Volume and Issue: unknown, P. 209 - 219

Published: Jan. 3, 2025

The consumption of energy in the residential area causes adverse impacts on environment. mitigation or maintenance power can be main step to preserve electricity for future and proper supply. In context with this, work focuses predicting novel hybrid tactic. tactic is integration Temporal Fusion Transformer (TFT) Convolutional Neural Network (CNN) (HTFT-CNN). This developed predict usage across varying time frames grip a multivariate series individual areas. proposed HTFT-CNN implemented combine both feature temporal-based data utilized observe intricate patterns. Attention mechanism (AM) fusion features that are obtained using multi-step (k=24) input sequences k=24 length sequence at 24 hours. Simulations conducted analyze robustness forecasting accuracy designed model parameters such as Root Mean Square error (RMSE), Absolute Percentage Error (MAPE). analyzed performance depicts design used planning management minimized RMSE MAPE values.

Language: Английский

Citations

1
Generalizable Wind Power Estimation from Historic Meteorological Data by Advanced Artificial Neural Networks DOI
Mert Akın İnsel,

Burcin Melek Ozturk,

Özgün Yücel

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122995 - 122995

Published: March 1, 2025

Language: Английский

Citations

0
Combined multi-component composite time series power prediction model for distributed energy systems based on STL data decomposition DOI Creative Commons

T. J. Yang,

Liansheng Huang,

Peng Fu

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117299 - 117299

Published: April 1, 2025

Language: Английский

Citations

0
Interpretable wind speed forecasting through two-stage decomposition with comprehensive relative importance analysis DOI
Huanze Zeng, Binrong Wu, Haoyu Fang

et al.

Applied Energy, Journal Year: 2025, Volume and Issue: 392, P. 126015 - 126015

Published: May 5, 2025

Language: Английский

Citations

0