Results 81 to 90 of about 406 (163)

RMF-Net: Regional Multi-Mode Fusion Network for Fractal-Aware EEG Motor Imagery Decoding

Fractal and Fractional
Motor Imagery (MI) decoding based on electroencephalogram (EEG) is promising for Brain–Computer Interface (BCI) applications, yet existing methods generally suffer from two major limitations.
Yingqi Zhang, Xuhui Wang, Enze Shi
doaj   +1 more source

A Transfer Learning Enhanced Decomposition-Based Hybrid Framework for Forecasting Multiple Time-Series

, 2023
Time-series forecasting is a challenging task that requires high accuracy and efficiency. Hybrid models that combine decomposition algorithms with multiple individual models have demonstrated promising results for forecasting performance.
Y He (7724882), Zili Zhang (13101534), L Tao (9648497)   +2 more
core  

Data-driven multivariate time series prediction of in-vehicle equipment failure rates

Journal of Engineering and Applied Science
Effectively predicting the failure rate of train-controlled on-board equipment is of great significance for rationally allocating equipment spares, drawing up maintenance plans, and reducing the occurrence of failures.
Yongfei Guo, Yonggang Chen, Haiyong Wang, Yang Liu   +3 more
doaj   +1 more source

A Predictive Model for Voltage Transformer Ratio Error Considering Load Variations

World Electric Vehicle Journal
The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions.
Zhenhua Li, Jiuxi Cui, Paulo R. F. Rocha, Ahmed Abu-Siada, Hongbin Li, Li Qiu   +5 more
doaj   +1 more source

Evaluation of the Impact of Multi-Timescale Wind Power Fluctuations on System Frequency Based on Multi-Variational Mode Decomposition Algorithm

IEEE Access
The increasing proportion of wind power in the power grid diminishes system inertia, posing significant challenges to system frequency stability.
Rui Zhang, Jifeng Liang, Baochao Zhang, Tengkai Yu, Naixin Zhang, Xiangdong Wang   +5 more
doaj   +1 more source

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

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   +1 more source

New approaches and prospects for the treatment of myxomatous degeneration of the mitral valve in dogs

Біологія тварин
Myxomatous mitral valve degeneration (MMVD) is the most common acquired heart disease in small and medium-sized dogs, leading to the development of chronic heart failure. The article summarizes current data (2020–2025) on new directions in the diagnosis,
N. I. Suslova, O. V. Semionov
doaj   +1 more source

Correlation of Morris and Macruz indices with the ae/ao ratio in dogs with myxomatous mitral valve disease

Macruz and Morris indices are electrocardiographic measures used in medicine that suggest the presence of left atrial remodeling. In dogs, the main cause of left atrial remodeling is mitral valve myxomatous degeneration (MVMD), with electrocardiography ...
João Vitor de Jesus Pais, Maria Júlia Tebet Boccaletti, Rodrigo Prevedello Franco, Camila Dias Porto, Cláudia Sampaio Fonseca Repetti, Carlos Eduardo de Siqueira, Isabela Bazzo da Costa, Patrícia Cincotto dos Santos Bueno, Beatriz Teixeira Martuchi   +8 more
core   +1 more source

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

Sensors (Basel), 2022
Yang X, Yuan R, Lv Y, Li L, Song H.
europepmc   +1 more source

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

Sci Rep, 2023
Eriksen T, Rehman NU.
europepmc   +1 more source