Results 151 to 160 of about 24,295 (253)

An Improved Fast Computational Method for Vibration Characteristic Analysis of Dry‐Type Iron Core Reactor

High Voltage, EarlyView.
ABSTRACT Structural mechanics field simulation plays a critical role in the vibration characteristic analysis of electrical equipment. Existing structural field analysis of equipment based on numerical simulation faces challenges such as convergence difficulties and prolonged computational time, failing to meet the demand for real‐time prediction of ...
Wanqing Wang, Caibo Liao, Bang Liu, Kai Li, Wenyu Liu, Zhaoguo Li, Xianfa Tian   +6 more
wiley   +1 more source

Explainable Hierarchical Graph Neural Networks for Structured Decision Modeling

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Decision modeling in complex systems involves heterogeneous factors with different degrees of controllability and structural dependence, yet most neural models treat all inputs uniformly and provide limited decision-level interpretability. We propose an
Sirisha Velampalli, Rakesh Gamidi
doaj  

Recognition of Spatiotemporal Feature Images of Zero‐Sequence Voltage for Single‐Phase High‐Impedance Ground Faults Under Complex Conditions

High Voltage, EarlyView.
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li, Yijia Cao, Chun Chen, Weiyu Wang, Yansha Li, Jinglu Li   +5 more
wiley   +1 more source

A Novel Converter Transformer DAM‐LSTNet Vibration Generation Model for Data Imbalance Identification

High Voltage, EarlyView.
ABSTRACT Converter transformer vibration failures, primarily because of winding and core vibrations, severely impact the safe operation of high voltage direct current (HVDC) systems. These vibrations are influenced by voltage and current, and are transmitted through transformer oil and structural components to the tank. Current numerical models fail to
Peiyu Jiang, Fanghui Yin, Liming Wang
wiley   +1 more source

Deep Learning for Parkinson's Disease Diagnosis: A Graph Neural Network (GNN) Based Classification Approach with Graph Wavelet Transform (GWT) Using Protein-Peptide Datasets. [PDF]

Diagnostics (Basel)
Mohanraj P, Raman V, Ramanathan S.
europepmc   +1 more source

A Theoretical Approach for Structuring and Analysing Knowledge Provenance for Visual Analytics

Computer Graphics Forum, EarlyView.
VAKG unfolds the interactions within the current knowledge model (A) into a temporal knowledge graph (B), which is structured as a 4‐way graph containing two temporal (green) and two static (yellow) knowledge graphs. By using VAKG, one can structure and store the user's knowledge‐gathering process and all related interactions for eventual analysis (C).
L. Christino, S. Rezaeipour, E. Milios, F. Paulovich   +3 more
wiley   +1 more source

Sequential Outlier Detection in Nonstationary Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT A novel method for sequential outlier detection in nonstationary time series is proposed. The method tests the null hypothesis of “no outlier” at each time point, addressing the multiple testing problem by bounding the error probability of successive tests, using extreme‐value theory. The asymptotic properties of the test statistic are studied
Florian Heinrichs, Patrick Bastian, Holger Dette   +2 more
wiley   +1 more source

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

EconoGNN: A graph neural network framework for temporal economic resilience insights. [PDF]

PLoS One
Araujo M, Rodrigues F, Sousa E.
europepmc   +1 more source

scMOG: A graph neural network method for regulatory relationship‐preserving single‐cell multi‐omics integration

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell multi‐omics sequencing technology provides a powerful tool for studying cellular heterogeneity. However, beyond the challenges of sparsity, heterogeneity, and dimensionality differences, a critical challenge in multi‐omics data integration lies in preserving the true regulatory relationships among molecular features.
Yucheng Lu, Xun Zhang, Hongwei Li
wiley   +1 more source