Results 71 to 80 of about 4,786,449 (207)

Simultaneous Multi–Horizon Forecasting of Dst and Hp60 Geomagnetic Indices via a Multitask LSTM Framework

Space Weather, Volume 24, Issue 8, August 2026.
Abstract This study presents a novel multitask deep learning framework that integrates models designed for simultaneous, multi‐horizon forecasting of Hp60 and Disturbance storm time (Dst) indices with lead times up to 3 hr. Using a Long Short‐Term Memory architecture, the models capture both mid‐latitude variability and the ring current dynamics. Input
Joseph Kagotho Muriithi, Collins Mito, Edward Uluma, Boniface Ndinya, Daniel Okoh   +4 more
wiley   +1 more source

Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition

Shock and Vibration, 2016
This study explores the capacity of the improved empirical mode decomposition (EMD) in railway wheel flat detection. Aiming at the mode mixing problem of EMD, an EMD energy conservation theory and an intrinsic mode function (IMF) superposition theory are
Yifan Li, Jianxin Liu, Yan Wang
doaj   +1 more source

Pixel‐Level Inversion Assessment for Ageing of Composite Insulator Sheds of Power System

High Voltage, Volume 11, Issue 4, Page 1021-1031, August 2026.
ABSTRACT The polymeric materials used in insulator sheds are prone to ageing under different environmental conditions, which can lead to flashovers and grid outages. The ageing process in composite insulators primarily involves changes in the microscopic properties of the materials.
Yang Liu, Yujun Guo, Yihan Fan, Chenguang Yang, Enming Bai, Song Xiao, Xueqin Zhang, Guoqiang Gao, Guangning Wu   +8 more
wiley   +1 more source

Correction of blink artifacts using independent component analysis and empirical mode decomposition. [PDF]

Blink-related ocular activity is a major source of artifacts in electroencephalogram (EEG) data. Independent component analysis (ICA) is a well-known technique for the correction of such ocular artifacts, but one of the limitations of ICA is that the ICs
Bhattacharya, Joydeep, Lindsen, Job P.
core   +6 more sources

Deep Neural Network-Based Empirical Mode Decomposition for Motor Imagery EEG Classification

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Motor imagery refers to the brain’s response during the mental simulation of physical activities, which can be detected through electroencephalogram (EEG) signals.
Hyunsoo Yu, Suwhan Baek, Jiwoon Lee, Illsoo Sohn, Bosun Hwang, Cheolsoo Park   +5 more
doaj   +1 more source

Interactive segmentation of membrane and membrane‐mimic densities in cryo‐EM maps

Acta Crystallographica Section D, Volume 82, Issue 8, Page 848-861, August 2026.
SURFER performs automated segmentation of contextual membrane and membrane‐mimic density in cryo‐EM maps to enable robust separation of macromolecular signal from surrounding detergent or lipid–membrane features. It is conveniently distributed as a plugin for UCSF ChimeraX, allowing interactive application within standard map‐visualization workflows ...
Alok Bharadwaj, Lotte Veerbeek, Arjen Jakobi   +2 more
wiley   +1 more source

Application of empirical mode decomposition in improving group method of data handling

, 2023
The accuracy of electricity load demand forecasting is essential for avoiding energy waste and overuse. Hence, this paper aims to model the forecast electricity load demand by combining Empirical Mode Decomposition (EMD) with Group Method of Data ...
Shabri, Ani, Razif, Nur Rafiqah Abdul
core   +1 more source

Enriching historical biologging datasets on seabirds using deep neural networks: A transformer‐based approach to infer energy expenditure proxy from GPS and environmental data

Methods in Ecology and Evolution, Volume 17, Issue 8, Page 2408-2423, August 2026.
Abstract Recent advances in biologging have led to the widespread use of accelerometers, which generate high‐resolution movement data essential for understanding animal behaviour. Derived from tri‐axial accelerometry, Overall Dynamic Body Acceleration (ODBA) serves as a proxy for energy expenditure that is less invasive and more cost‐effective than ...
Noémie Muquet, Adrien Brunel, Christophe Barbraud, Leandro Bugoni, Karine Delord, Guilherme Tavares Nunes, Jean‐Daniel Zucker, Sophie Lanco   +7 more
wiley   +1 more source

Secondary Hybrid Decomposition Strategy for Wind Power Prediction Using Long Short-Term Memory With Crisscross Optimization

IEEE Access
This paper presents a hybrid forecasting model for a wind power named Secondary Hybrid Decomposition (SHD)-Long Short-Term Memory (LSTM) with Crisscross Optimization (CSO).The model integrates three key techniques to improve prediction accuracy. Firstly,
Yoseph Mekonnen Abebe, Habtamu Kassa Bayu, Tekalign Tesfaye Mengistu, Abera Tullu, Sunghun Jung   +4 more
doaj   +1 more source

Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance

EURASIP Journal on Advances in Signal Processing, 2008
For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by using wavelet denoising method to avoid the mode ...
Chen Ming, Lin Yan, Qin Pinle
doaj   +1 more source