Deep learning hybrid models with multivariate variational mode decomposition for estimating daily solar radiation [PDF]
Alexandria Engineering JournalSolar 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 +6 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
Prediction of Sea Level Using Double Data Decomposition and Hybrid Deep Learning Model for Northern Territory, Australia [PDF]
MathematicsSea level rise (SLR) attributed to the melting of ice caps and thermal expansion of seawater is of great global significance to vast populations of people residing along the world’s coastlines.
Nawin Raj +3 more
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction [PDF]
长江科学院院报[Objective] This study took Hanjiang River Basin as the study area. To better monitor the runoff conditions in Hanjiang River Basin, the daily runoff data collected from Ankang and Baihe hydroelectric power stations were selected for prediction analysis.
DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en
doaj +3 more sources
Fault-Line Selection Method in Active Distribution Networks Based on Improved Multivariate Variational Mode Decomposition and Lightweight YOLOv10 Network [PDF]
EnergiesIn active distribution networks (ADNs), the extensive deployment of distributed generations (DGs) heightens system nonlinearity and non-stationarity, which can weaken fault characteristics and reduce fault detection accuracy.
Sizu Hou, Wenyao Wang
doaj +2 more sources
Early fault diagnosis of transformer windings based on the improved MVMD-ELM [PDF]
Frontiers in Energy ResearchAiming at the problems of weak early fault characteristics of transformer windings, large noise interference and insufficient accuracy of traditional diagnostic methods, this paper proposes an early fault diagnosis method for transformer windings based ...
Qiuyang Lin +7 more
doaj +2 more sources
A Predictive Model for Voltage Transformer Ratio Error Considering Load Variations [PDF]
World Electric Vehicle JournalThe accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions.
Zhenhua Li +5 more
doaj +2 more sources
A Noise Reduction Algorithm for White Noise and Periodic Narrowband Interference Noise in Partial Discharge Signals [PDF]
Applied SciencesPartial discharge (PD) detection plays an important role in online condition monitoring of electrical equipment and power cables. However, the noise of PD measurement will significantly reduce the performance of the detection algorithm. In this paper, we
Jiyuan Cao +3 more
doaj +2 more sources
Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach [PDF]
, 2022 Accurate forecasting of the wave energy is crucial and has significant potential because every wave meter possesses an energy amount ranging from 30 to 40 kW along the shore.
Yaseen, Zaher Mundher +5 more
core +3 more sources
Multivariate Nonlinear Sparse Mode Decomposition and Its Application in Gear Fault Diagnosis
IEEE Access, 2021 Multi-channel signal has more abundant and accurate state characteristic information than single channel signal. How to separate fault characteristic information from the multi-channel signal is the key of fault diagnosis.
Haiyang Pan +3 more
doaj +1 more source