A Hybrid Model Based on Complete Ensemble Empirical Mode Decomposition With Adaptive Noise, GRU Network and Whale Optimization Algorithm for Wind Power Prediction
To ensure the safe and stable operation of power systems, accurate prediction of wind power generation is particularly important. However, due to the randomness, fluctuation, and intermittency of wind energy, as well as the challenges in determining the hyperparameters of the gated recurrent unit (G...
Main Authors: | Andi Sheng, Lewei Xie, Yixiang Zhou, Zhen Wang, Yuechao Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10155125/ |
Similar Items
-
Stock Price Prediction Using a Frequency Decomposition Based GRU Transformer Neural Network
by: Chengyu Li, et al.
Published: (2022-12-01) -
A New Hybrid Approach for Short-Term Electric Load Forecasting Applying Support Vector Machine with Ensemble Empirical Mode Decomposition and Whale Optimization
by: Tongxiang Liu, et al.
Published: (2019-04-01) -
Ultra-Short-Term Wind Power Combined Prediction Based on Complementary Ensemble Empirical Mode Decomposition, Whale Optimisation Algorithm, and Elman Network
by: Anfeng Zhu, et al.
Published: (2022-04-01) -
An Accurate QRS Complex and P Wave Detection in ECG Signals Using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Approach
by: Md Billal Hossain, et al.
Published: (2019-01-01) -
Noise Elimination for Coalcutter Vibration Signal Based on Ensemble Empirical Mode Decomposition and an Improved Harris Hawks Optimization Algorithm
by: Jing Xu, et al.
Published: (2022-09-01)