Fault Feature Extraction Method for Rolling Bearings Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition. [PDF]
Sensors (Basel), 2023 Wang L, Li H, Xi T, Wei S.
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Advanced Intelligent Systems, EarlyView.A distributed wireless sensing framework enables noninvasive monitoring of plant salinity stress through leaf reflectance measurements acquired with portable optical sensors. The collected data are processed using TinyML‐based neural network models deployed at the edge, enabling accurate, real‐time, and low‐cost classification of salinity levels, while
Ali Ahmad +4 more
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A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning. [PDF]
Int J Environ Res Public Health, 2022 Liu S +5 more
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Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition. [PDF]
Front Physiol, 2023 Feng J +6 more
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, 2019 Expert systems in multi-scale runoff prediction are useful decision-making tools but the stochastic nature of hydrologic variables can pose challenges in attaining a reliable predictive model.
Deo, Ravinesh C. +6 more
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Bearing Fault Diagnosis Using Piecewise Aggregate Approximation and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise. [PDF]
Sensors (Basel), 2022 Hu L, Wang L, Chen Y, Hu N, Jiang Y.
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Angewandte Chemie International Edition, EarlyView.The overpotential constitutes an electrochemical potential difference at the solid–liquid interface, which can manifest itself in different ways. In general, it can not only drive the reaction along the reaction coordinate, but also modulate chemical potentials in the extended environment that shape activation barriers, without necessarily being a ...
Sebastian Z. Oener +10 more
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Ensemble All Time-Scale Decomposition Method and Its Application in Bevel Gear Fault Diagnosis
SensorsAll time-scale decomposition (ATD) is a non-parametric adaptive signal decomposition method, which relies on zero-crossing points and extreme points to jointly construct the baseline, achieving the suppression of modal mixing caused by the proximity of ...
Zhengyang Cheng +4 more
doaj +1 more source
A New Time Series Forecasting Model Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Temporal Convolutional Network. [PDF]
Neural Process Lett, 2022 Guo C, Kang X, Xiong J, Wu J.
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Business Strategy and the Environment, EarlyView.ABSTRACT This study examines the determinants of firms' propensity to adopt green buildings in the Euro Stoxx 300 and the S&P 500 indices, during 2012–2023. Using random forest binary classifiers, we assess the relative importance of financial, sectoral, geographic, and climate governance predictors and uncover nonlinear relationships often overlooked ...
María del Carmen Valls Martínez +3 more
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