Anomaly detection in current and voltage data is critical to ensuring the reliability and safety of electrical systems. This research presents a comprehensive framework that combines feature extraction and machine learning to identify irregularities in time series measurements. The study evaluates five anomaly detectio...
Krisdahim Kogoya, Yu-Hao Li, Hui Liu et al.· 2026 6th Power System and Gr...· 0 citations
GFE-Net is rigorously benchmarked on two widely adopted large-scale datasets—S3DIS and SensatUrban—yielding OA/mIoU of 89.6%/73.1% and 93.3%/61.1%, respectively.
It is suggested that the proposed hybrid dynamic-statistical reconstruction framework named interior+surface quasi-geostrophic (isQG)-empowered ResNet is a feasible and stable framework for subsurface reconstruction and is, thus, helpful for analyzing the three-dimensional structures of mesoscale phenomena.
Xiting Sun, T. Xie, Hengqian Yan et al.· IEEE Journal of Selected Top...· 0 citations
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