Results 31 to 40 of about 406 (163)

Deep learning hybrid models with multivariate variational mode decomposition for estimating daily solar radiation

Alexandria Engineering Journal
Solar energy is one of the renewable and clean energy sources. Accurate solar radiation (SR) estimates are therefore needed in solar energy applications.
Shahab S. Band, Sultan Noman Qasem, Rasoul Ameri, Hao-Ting Pai, Brij B. Gupta, Saeid Mehdizadeh, Amir Mosavi   +6 more
doaj   +2 more sources

Hybrid Feature‐Selection and Multi‐Scale Deep Learning for Carbon Price Forecasting in Emerging Carbon Markets

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
As global attention to CO2 intensifies, accurate carbon‐price forecasting has become a core topic in carbon‐market research. We propose a hybrid forecasting framework, extremely randomized trees (ET)–multivariate variational mode decomposition (MVMD)–gated recurrent unit (GRU), that integrates three advanced components to predict carbon prices for ...
Sensheng Li, Minjun Huang, Fuping Wang, Junkun Hu, Hanyue Wang, Houjian Li, Cheng Du   +6 more
wiley   +2 more sources

Enhanced Deep Representation Learning Extreme Learning Machines for EV Charging Load Forecasting by Improved Artemisinin Optimization and Multivariate Variational Mode Decomposition

Energies
The Electric Vehicle (EV) industry is developing rapidly, and EVs are becoming an increasingly important choice for the future of transportation. Therefore, accurately forecasting the electricity demand for EVs is crucial.
Anjie Zhong, Honghai Li, Zhongyi Tang, Zhirong Zhang   +3 more
doaj   +2 more sources

Series-Core Fusion Based Multivariate Variational Mode Decomposition for Short-Term Wind Power Prediction Using Multiple Meteorological Data

Forecasting
Accurate wind power forecasting is critical for enhancing the operational efficiency and stability of electrical power grids. Conventional single-variable signal decomposition forecasting methods ignore the coupling relationship between wind power and ...
Wentian Lu, Zhenming Lu, Wenjie Liu, Yifeng Cao   +3 more
doaj   +2 more sources

Seismic Random Noise Denoising Using Mini-Batch Multivariate Variational Mode Decomposition. [PDF]

Comput Intell Neurosci, 2022
Seismic noise attenuation plays an important role in seismic interpretation. The empirical mode decomposition, synchrosqueezing wavelet transform, variational mode decomposition, etc., are often applied trace by trace. Multivariate empirical mode decomposition, multivariate synchrosqueezing wavelet transform, and multivariate variational mode ...
Wu G, Liu G, Wang J, Fan P.
europepmc   +2 more sources

Short-Term Load Forecasting for a Renewable-Rich Power System Using an IMVMD-XLSTM

Energies
The high penetration of photovoltaic and wind power introduces strong non-stationarity and multi-scale fluctuations into power system load profiles, challenging the accuracy of short-term load forecasting (STLF).
Qiujing Lin, Hongquan Zhu, Xiaolong Wang, Xiangang Peng   +3 more
doaj   +2 more sources

Time-Domain Electromagnetic Noise Suppression Using Multivariate Variational Mode Decomposition

Remote Sensing
Noise suppression is essential in time-domain electromagnetic (TDEM) data processing and interpretation. TDEM data are typically in broadband signal, which makes it difficult to separate the signal in the whole frequency band.
Kang Xing, Shiyan Li, Zhijie Qu, Xiaojuan Zhang   +3 more
doaj   +2 more sources

DYNAMIC UNBALANCE DETECTION OF CARDAN SHATF IN HIGH-SPEED TRAIN BASED ON MODIFIED VARIATIONAL MODE DECOMPOSITION

Jixie qiangdu, 2017
Aiming at the adverse influence of penalty parameter and mode number on the VMD（ variational mode decomposition）,a newly MVMD（ modification variational mode decomposition） was proposed through the information entropy difference.
HONG JianFeng, DING JianMing, LIN JianHui, ZHENG ShuBin   +3 more
doaj   +2 more sources

Detecting and Diagnosing Process Nonlinearity- Induced Unit-Wide Oscillations Based on an Optimized Multivariate Variational Mode Decomposition Method

IEEE Access, 2022
In process control system, nonlinearity-induced unit-wide oscillations are a common fault, which degrades the control performance and threaten the stability.
Zhuliang Lin, Min Sun, Xialai Wu
doaj   +1 more source

Seismic attenuation estimation using multivariate variational mode decomposition

Frontiers in Earth Science, 2022
A seismic attenuation estimation approach is proposed based on multivariate variational mode decomposition (MVMD). MVMD, as a multivariable or multichannel signal processing tool, can extract several predefined multivariable modulation oscillations from ...
Jun-Zhou Liu, Jun-Zhou Liu, Jun-Zhou Liu, Ya-juan Xue, Lei Shi, Lei Shi, Lei Shi, Lei Han, Lei Han, Lei Han   +9 more
doaj   +1 more source