Results 21 to 30 of about 16,203 (295)

Airborne Radio-Echo Sounding Data Denoising Using Particle Swarm Optimization and Multivariate Variational Mode Decomposition [PDF]

Remote Sensing, 2023
Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode
Yuhan Chen, Sixin Liu, Kun Luo, Lijuan Wang, Xueyuan Tang   +4 more
doaj   +2 more sources

Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology [PDF]

Energy Reports, 2021
Forecasting of solar radiation (Radn) can provide an insight vision for the amount of green and friendly energy sources. Owing to the non-linearity and non-stationarity challenges caused by meteorological variables in forecasting Radn, a variational mode
Mumtaz Ali, Ramendra Prasad, Yong Xiang, Mohsin Khan, Aitazaz Ahsan Farooque, Tianrui Zong, Zaher Mundher Yaseen   +6 more
doaj   +2 more sources

A High-Precision Short-Term Photovoltaic Power Forecasting Model Based on Multivariate Variational Mode Decomposition and Gated Recurrent Unit-Attention with Crested Porcupine Optimizer-Enhanced Vector Weighted Average Algorithm. [PDF]

Sensors (Basel)
The increasing reliance on renewable energy sources, such as photovoltaic (PV) systems, is pivotal for achieving sustainable development and addressing global energy challenges. However, short-term power forecasting for distributed PV systems often faces
Pian J, Chen X.
europepmc   +3 more sources

Subsynchronous Oscillation Source Location in Power System with High Penetration of Wind Power Using Multivariate Variational Mode Decomposition [PDF]

IEEE Transactions on Power Systems
Accurately and promptly extracting subsynchronous oscillation (SSO) components from measurements and locating SSO sources are crucial for SSO suppression.
Pons, Enrico, Li, Xue, Liu, Bohan, Jiang, Tao, Huang, Tao, Li, Guoqing, Mazza, Andrea   +6 more
core   +2 more sources

Exploring functional connectivity at different timescales with multivariate mode decomposition [PDF]

Frontiers in Neuroscience
This 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, Kristian Frølich, Naveed ur Rehman   +2 more
doaj   +2 more sources

Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold [PDF]

Meitan xuebao
The insulation state of the mine cable plays an important role in the stable operation of the mine power supply system. Partial discharge on-line monitoring is an important means of cable insulation state monitoring.
Jiyuan CAO, Yanwen WANG, Peng CHEN, Xuan ZHOU, Weixiong ZHU, Yihe ZHANG, Le WANG   +6 more
doaj   +3 more sources

Advanced ADHD Detection Using Multivariate Variational Mode Decomposition and Deep Learning: A Novel EEG-Based Framework [PDF]

InfoScience Trends
This study proposes a novel framework for detecting Attention Deficit Hyperactivity Disorder (ADHD) using electroencephalography (EEG) signals, integrating multivariate variational mode decomposition (MVMD) with machine learning techniques.
Parastou Shahmohamadi, Shiva Amini, Shiva Khanbabaee, Negin Tavakoli, Sedigheh Molaei, Niloofar Teimoori   +5 more
doaj   +2 more sources

A Novel Multivariate Cutting Force-Based Tool Wear Monitoring Method Using One-Dimensional Convolutional Neural Network [PDF]

Sensors, 2022
Tool wear condition monitoring during the machining process is one of the most important considerations in precision manufacturing. Cutting force is one of the signals that has been widely used for tool wear condition monitoring, which contains the ...
Xu Yang, Rui Yuan, Yong Lv, Li Li, Hao Song   +4 more
doaj   +2 more sources

Data-driven nonstationary signal decomposition approaches: a comparative analysis [PDF]

Scientific Reports, 2023
Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent amplitude- and frequency-modulated components. This represents an important preprocessing step in many practical signal processing pipelines, providing ...
Thomas Eriksen, Naveed ur Rehman
doaj   +2 more sources

Multivariate variational mode decomposition to extract the stripe noise in GRACE harmonic coefficients

Geophysical Journal International
SUMMARY In this work, a novel method has been developed to remove the north–south stripe noise in the Level-2 spherical harmonic coefficient products collected by the Gravity Recovery and Climate Experiment (GRACE) mission. The proposed method extracts the stripe noise from the equivalent water height (EWH) map via the Multivariate ...
Guangyu Jian, Fang Zou, Chuang Xu, Zhengwen Yan   +3 more
openaire   +4 more sources