Wind Speed Forecasting Based on Data Decomposition and Deep Learning Models: A Case Study of a Wind Farm in Saudi Arabia
Fuente:
arXiv
Saved in:
| Main Authors: | Aldossary, Yasmeen, Hewahi, Nabil, Alasaadi, Abdulla |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits
by: Musaaed, Elham, et al.
Published: (2024)
by: Musaaed, Elham, et al.
Published: (2024)
Legendre Memory Unit with A Multi-Slice Compensation Model for Short-Term Wind Speed Forecasting Based on Wind Farm Cluster Data
by: Zhang, Mumin, et al.
Published: (2026)
by: Zhang, Mumin, et al.
Published: (2026)
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions
by: Malakar, Sourav, et al.
Published: (2024)
by: Malakar, Sourav, et al.
Published: (2024)
Deep Learning for Modeling and Dispatching Hybrid Wind Farm Power Generation
by: Lawrence, Zach, et al.
Published: (2025)
by: Lawrence, Zach, et al.
Published: (2025)
Tube Loss based Deep Networks For Improving the Probabilistic Forecasting of Wind Speed
by: Anand, Pritam, et al.
Published: (2025)
by: Anand, Pritam, et al.
Published: (2025)
Learning to Optimise Wind Farms with Graph Transformers
by: Li, Siyi, et al.
Published: (2023)
by: Li, Siyi, et al.
Published: (2023)
A Novel Machine Learning Classifier Based on Genetic Algorithms and Data Importance Reformatting
by: Alkhayyata, A. K., et al.
Published: (2024)
by: Alkhayyata, A. K., et al.
Published: (2024)
Enhancing Wind Speed and Wind Power Forecasting Using Shape-Wise Feature Engineering: A Novel Approach for Improved Accuracy and Robustness
by: Christian, Mulomba Mukendi, et al.
Published: (2024)
by: Christian, Mulomba Mukendi, et al.
Published: (2024)
Inter-turbine Modelling of Wind-Farm Power using Multi-task Learning
by: Brealy, Simon M., et al.
Published: (2025)
by: Brealy, Simon M., et al.
Published: (2025)
A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting
by: Chen, Yinsong, et al.
Published: (2026)
by: Chen, Yinsong, et al.
Published: (2026)
TCNFormer: Temporal Convolutional Network Former for Short-Term Wind Speed Forecasting
by: Zim, Abid Hasan, et al.
Published: (2024)
by: Zim, Abid Hasan, et al.
Published: (2024)
WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting
by: Fan, Hang, et al.
Published: (2025)
by: Fan, Hang, et al.
Published: (2025)
On Additive Gaussian Processes for Wind Farm Power Prediction
by: Brealy, Simon M., et al.
Published: (2026)
by: Brealy, Simon M., et al.
Published: (2026)
Self-attentive Transformer for Fast and Accurate Postprocessing of Temperature and Wind Speed Forecasts
by: Van Poecke, Aaron, et al.
Published: (2024)
by: Van Poecke, Aaron, et al.
Published: (2024)
Probabilistic Wind Power Forecasting with Tree-Based Machine Learning and Weather Ensembles
by: Bruninx, Max, et al.
Published: (2026)
by: Bruninx, Max, et al.
Published: (2026)
Operational Wind Speed Forecasts for Chile's Electric Power Sector Using a Hybrid ML Model
by: Suri, Dhruv, et al.
Published: (2024)
by: Suri, Dhruv, et al.
Published: (2024)
Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations
by: Nilsen, Marcus Binder, et al.
Published: (2026)
by: Nilsen, Marcus Binder, et al.
Published: (2026)
Climate-based Pre-screening of Self-sustaining Regreening Opportunities in Drylands: A Case Study for Saudi Arabia
by: Froehlich, Katja, et al.
Published: (2026)
by: Froehlich, Katja, et al.
Published: (2026)
Short-term Wind Speed Forecasting for Power Integration in Smart Grids based on Hybrid LSSVM-SVMD Method
by: Yekun, Ephrem Admasu, et al.
Published: (2024)
by: Yekun, Ephrem Admasu, et al.
Published: (2024)
Probabilistic Multi-Layer Perceptrons for Wind Farm Condition Monitoring
by: Fiocchi, Filippo, et al.
Published: (2024)
by: Fiocchi, Filippo, et al.
Published: (2024)
Hybrid Transformer Network for Different Horizons-based Enriched Wind Speed Forecasting
by: Madhiarasan, M., et al.
Published: (2022)
by: Madhiarasan, M., et al.
Published: (2022)
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
by: Monroc, Claire Bizon, et al.
Published: (2025)
by: Monroc, Claire Bizon, et al.
Published: (2025)
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data
by: Lehmann, Nils, et al.
Published: (2024)
by: Lehmann, Nils, et al.
Published: (2024)
Attention is All You Need to Optimize Wind Farm Operations and Maintenance
by: Kazemian, Iman, et al.
Published: (2024)
by: Kazemian, Iman, et al.
Published: (2024)
WindMiL: Equivariant Graph Learning for Wind Loading Prediction
by: Vargiemezis, Themistoklis, et al.
Published: (2025)
by: Vargiemezis, Themistoklis, et al.
Published: (2025)
Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms
by: Nilsen, Marcus Binder, et al.
Published: (2026)
by: Nilsen, Marcus Binder, et al.
Published: (2026)
Quantifying the Influences on Probabilistic Wind Power Forecasts
by: Schreiber, Jens, et al.
Published: (2018)
by: Schreiber, Jens, et al.
Published: (2018)
Graph Neural Networks in Wind Power Forecasting
by: Castellano, Javier, et al.
Published: (2025)
by: Castellano, Javier, et al.
Published: (2025)
STDHL: Spatio-Temporal Dynamic Hypergraph Learning for Wind Power Forecasting
by: Dong, Xiaochong, et al.
Published: (2024)
by: Dong, Xiaochong, et al.
Published: (2024)
Marginalize, Rather than Impute: Probabilistic Wind Power Forecasting with Incomplete Data
by: Wen, Honglin, et al.
Published: (2024)
by: Wen, Honglin, et al.
Published: (2024)
Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental Data
by: Mo, Yaxin, et al.
Published: (2024)
by: Mo, Yaxin, et al.
Published: (2024)
DiffScale: Continuous Downscaling and Bias Correction of Subseasonal Wind Speed Forecasts using Diffusion Models
by: Springenberg, Maximilian, et al.
Published: (2025)
by: Springenberg, Maximilian, et al.
Published: (2025)
Applying Ensemble Models based on Graph Neural Network and Reinforcement Learning for Wind Power Forecasting
by: Song, Hongjin, et al.
Published: (2025)
by: Song, Hongjin, et al.
Published: (2025)
Quantum Neural Networks for Wind Energy Forecasting: A Comparative Study of Performance and Scalability with Classical Models
by: Hangun, Batuhan, et al.
Published: (2025)
by: Hangun, Batuhan, et al.
Published: (2025)
DeepMIDE: A Multi-Output Spatio-Temporal Method for Ultra-Scale Offshore Wind Energy Forecasting
by: Ye, Feng, et al.
Published: (2024)
by: Ye, Feng, et al.
Published: (2024)
Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
by: Mole, Andrew, et al.
Published: (2025)
by: Mole, Andrew, et al.
Published: (2025)
Explainable Modeling for Wind Power Forecasting: A Glass-Box Approach with High Accuracy
by: Liao, Wenlong, et al.
Published: (2023)
by: Liao, Wenlong, et al.
Published: (2023)
Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed
by: Goldwyn, Harrison J., et al.
Published: (2025)
by: Goldwyn, Harrison J., et al.
Published: (2025)
An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting
by: Zhu, Qiyuan, et al.
Published: (2024)
by: Zhu, Qiyuan, et al.
Published: (2024)
Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields
by: Zambra, Matteo, et al.
Published: (2023)
by: Zambra, Matteo, et al.
Published: (2023)
Similar Items
-
A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits
by: Musaaed, Elham, et al.
Published: (2024) -
Legendre Memory Unit with A Multi-Slice Compensation Model for Short-Term Wind Speed Forecasting Based on Wind Farm Cluster Data
by: Zhang, Mumin, et al.
Published: (2026) -
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions
by: Malakar, Sourav, et al.
Published: (2024) -
Deep Learning for Modeling and Dispatching Hybrid Wind Farm Power Generation
by: Lawrence, Zach, et al.
Published: (2025) -
Tube Loss based Deep Networks For Improving the Probabilistic Forecasting of Wind Speed
by: Anand, Pritam, et al.
Published: (2025)