Results 11 to 20 of about 10,183 (167)
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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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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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
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Forecasting of interval carbon price in China based on decomposition-reconstruction-ensemble framework [PDF]
Carbon Balance and ManagementAccurate prediction of carbon prices is imperative for the effective management of carbon markets and the facilitation of a global transition to green energy.
Beibei Hu, Yunhe Cheng
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Noise-Assisted Multivariate Variational Mode Decomposition [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 The variational mode decomposition (VMD) is a widely applied optimization-based method, which analyzes non-stationary signals concurrently. Correspondingly, its recently proposed multivariate extension, i.e., MVMD, has shown great potentials in analyzing multichannel signals.
Zisou, Charilaos A. +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 Variational Mode Decomposition [PDF]
IEEE Transactions on Signal Processing, 2019 In this paper, a generic extension of variational mode decomposition (VMD) algorithm for multivariate or multichannel data sets is presented. We first define a model for multivariate modulated oscillations that is based on the presence of a joint or common frequency component among all channels of input data.
Naveed ur Rehman, Hania Aftab
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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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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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Energy Reports, 2022 Peak load forecasting plays an integral part in the planning and operating of energy plants for the utility companies and policymakers to devise reliable and stable power infrastructure.
M. Zulfiqar +4 more
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