Results 141 to 150 of about 220,761 (282)
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
The traction power supply system of railways operating with a mix of AC-DC-AC and AC-DC electric locomotives frequently encounters train-traction network resonance due to the presence of harmonic currents across a wide frequency domain.
LONG Lilan +3 more
doaj
Fault Diagnosis of Traction Transformer Based on Bayesian Network
As the core equipment of a traction power supply system, the traction transformer is very important to ensure the safe and reliable operation of the system. At present, the three-ratio method is mainly used to distinguish transformer faults, whereas such a method has some defects, such as insufficient coding and over-general fault classification.
openaire +1 more source
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
Low-frequency oscillation of train–network system considering traction power supply mode
The low-frequency oscillation (LFO) has occurred in the train–network system due to the introduction of the power electronics of the trains. The modeling and analyzing method in current researches based on electrified railway unilateral power supply ...
Yuchen Liu +3 more
doaj +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationary. A Minimum Distance to Mean classifier on covariance manifolds uses geodesic distances to outperform convolutional neural networks while reducing ...
Arnau Marin‐Llobet +9 more
wiley +1 more source
Based on the harmonic source of converter’s modulation voltage of AC electric locomotive, it discussed the generation principles of high frequency resonance voltage of traction network.
JIANG Jiajiu, CHEN Hanqin, WAN Guang
doaj

