Enhanced forecasting of shipboard electrical power demand using multivariate input and variational mode decomposition with mode selection [PDF]
Scientific ReportsAccurate forecasting of shipboard electricity demand is essential for optimizing Energy Management Systems (EMSs), which are crucial for efficient and profitable operation of shipboard power grids. To address this challenge, this paper introduces a novel
Paolo Fazzini +3 more
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A Novel EMG-Based Hand Gesture Recognition Framework Based on Multivariate Variational Mode Decomposition [PDF]
Sensors, 2021 Surface electromyography (sEMG) is a kind of biological signal that records muscle activity noninvasively, which is of great significance in advanced human-computer interaction, prosthetic control, clinical therapy, and biomechanics.
Kun Yang +4 more
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Deep Learning Method Based on Multivariate Variational Mode Decomposition for Classification of Epileptic Signals [PDF]
Brain SciencesBackground/Objectives: Epilepsy is a neurological disorder that severely impacts patients’ quality of life. In clinical practice, specific pharmacological and surgical interventions are tailored to distinct seizure types.
Shang Zhang +3 more
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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 +9 more
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New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes [PDF]
Ecological Indicators, 2023 Reference evapotranspiration (ETo) is a vital climate parameter affecting plants' water use. ETo can generate large deficits in soil moisture and runoff in different regions and seasons, leading to uncertainties in drought warning systems.
Mumtaz Ali +8 more
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Fault Diagnosis of Wind Turbine Gearbox Based on Improved Multivariate Variational Mode Decomposition and Ensemble Refined Composite Multivariate Multiscale Dispersion Entropy [PDF]
EntropyWind turbine planetary gearboxes have complex structures and operating environments, which makes it difficult to extract fault features effectively. In addition, it is difficult to achieve efficient fault diagnosis.
Xin Xia, Xiaolu Wang, Weilin Chen
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition [PDF]
Scientific ReportsPermeability index (PI) and magnesium absorption ratio (MAR) are both primary irrigation water quality indicators (IWQI) used to evaluate the efficacy of agricultural water supplies.
Marjan Kordani +3 more
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Exploring functional connectivity at different timescales with multivariate mode decomposition [PDF]
Frontiers in NeuroscienceThis paper explores an alternative way for analyzing static Functional Connectivity (FC) in functional Magnetic Resonance Imaging (fMRI) data across multiple timescales using a class of adaptive frequency-based methods referred to as Multivariate Mode ...
Manuel Morante +2 more
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Scientific Reports, 2023 A novel detection method based on multivariate extended variational mode decomposition-based time–frequency images and incremental RVM algorithm (MEVMDTFI–IRVM) is presented for fault detection of gearbox.
Siwei Nao, Yan Wang
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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
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