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Articles

A Mamba-Driven Spatiotemporal Graph Neural Network for Fault Location in Low-Observability Active Distribution Networks

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By Jilong Ma, Xuguang Hu, Zhengying Hou
| preprints.org
You are already at the latest version In fault location for large-scale active distribution networks under low-observability conditions, inter-node relationships are difficult to model accurately, critical information at the initial fault stage is easily overlooked, and global information is insufficiently utilized. To address these issues, an adaptive Mamba-driven spatiotemporal graph neural network, termed AM-STGNN, is proposed.
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