Attention-Driven Hybrid Ensemble Approach With Bayesian Optimization for Accurate Energy Forecasting in Jeju Island’s Renewable Energy System
The rapid integration of renewable energy sources into power grids has created an urgent need for accurate energy demand and supply forecasting models capable of managing the inherent variability of renewable energy generation. The combination of fluctuating consumer demand patterns and high variabi...
Saved in:
Main Authors: | Muhammad Ali Iqbal, Joon-Min Gil, Soo Kyun Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10833637/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Harnessing AI for Enhanced Weather Prediction: A Focus on Rainfall
by: Hira Farman, et al.
Published: (2024-12-01) -
Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches
by: Diana Balioz
Published: (2022-12-01) -
The Use of Ensembles in Space Weather Forecasting
by: J. A. Guerra, et al.
Published: (2020-02-01) -
Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting
by: N. O. Edward‐Inatimi, et al.
Published: (2024-12-01) -
Research on Monthly Runoff Forecast in Beijiang River Basin Based on Multi-model Ensemble Method
by: ZHONG Yixuan, et al.
Published: (2022-01-01)