Results 81 to 90 of about 226 (142)

Short-term load forecasting using a metaheuristic optimized temporal fusion transformer with decomposition technique

Frontiers in Artificial Intelligence
Short-term load forecasting plays a vital role in today's modern life to ensure the balance between energy demand and supply. Dynamic variations in weather and electricity consumption patterns can significantly influence load patterns, resulting in ...
Radhika Chandrasekaran, Senthil Kumar Paramasivan   +1 more
doaj   +1 more source

Deep learning hybrid models with multivariate variational mode decomposition for estimating daily solar radiation

Alexandria Engineering Journal
Solar energy is one of the renewable and clean energy sources. Accurate solar radiation (SR) estimates are therefore needed in solar energy applications.
Shahab S. Band, Sultan Noman Qasem, Rasoul Ameri, Hao-Ting Pai, Brij B. Gupta, Saeid Mehdizadeh, Amir Mosavi   +6 more
doaj   +1 more source

Early fault diagnosis of transformer windings based on the improved MVMD-ELM

Frontiers in Energy Research
Aiming at the problems of weak early fault characteristics of transformer windings, large noise interference and insufficient accuracy of traditional diagnostic methods, this paper proposes an early fault diagnosis method for transformer windings based ...
Qiuyang Lin, Congwei Wang, Luyi Zhang, Fengping Zhang, Zichi Zhao, Minyi Wei, Jiaqi Liu, Cheng Li   +7 more
doaj   +1 more source

The SSHVEP Paradigm-Based Brain Controlled Method for Grasping Robot Using MVMD Combined CNN Model

IEEE Transactions on Neural Systems and Rehabilitation Engineering
In recent years, the steady-state visual evoked potentials (SSVEP) based brain control method has been employed to help people with disabilities because of its advantages of high information transmission rate and low training time.
Rui Li, Duanyang Bai, Zhijun Li, Shiqiang Yang, Weiping Liu, Yichi Zhang, Jincao Zhou, Jing Luo, Wen Wang   +8 more
doaj   +1 more source

Fault-Line Selection Method in Active Distribution Networks Based on Improved Multivariate Variational Mode Decomposition and Lightweight YOLOv10 Network

Energies
In active distribution networks (ADNs), the extensive deployment of distributed generations (DGs) heightens system nonlinearity and non-stationarity, which can weaken fault characteristics and reduce fault detection accuracy.
Sizu Hou, Wenyao Wang
doaj   +1 more source

Jump Plus AM-FM Mode Decomposition

A novel method for decomposing a nonstationary signal into amplitude- and frequency-modulated (AM-FM) oscillations and discontinuous (jump) components is proposed.
Korshøj, Anders Rosendal, Nazari, Mojtaba, Rehman, Naveed ur   +2 more
core  

Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence

Remote Sensing
Pacific Island countries are vulnerable to the impacts of climate change, which include the risks of increased ocean temperatures, sea level rise and coastal wetland loss.
Nawin Raj, Sarah Pasfield-Neofitou
doaj   +1 more source

Short-Term Load Forecasting for a Renewable-Rich Power System Using an IMVMD-XLSTM

Energies
The high penetration of photovoltaic and wind power introduces strong non-stationarity and multi-scale fluctuations into power system load profiles, challenging the accuracy of short-term load forecasting (STLF).
Qiujing Lin, Hongquan Zhu, Xiaolong Wang, Xiangang Peng   +3 more
doaj   +1 more source

Multiscale Functional Connectivity: Exploring the brain functional connectivity at different timescales

Human brains exhibit highly organized multiscale neurophysiological dynamics. Understanding those dynamic changes and the neuronal networks involved is critical for understanding how the brain functions in health and disease.
Frølich, Kristian, Morante, Manuel, Rehman, Naveed ur   +2 more
core  

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

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