Missing data-aware robust electrical load forecasting based on hierarchical downsampling-upsampling spatiotemporal graph network

doi:10.1016/j.apenergy.2025.127209

2025-12-17

PRE

DOI：10.1016/j.apenergy.2025.127209

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摘要

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• 提出HDU-STGNN，一种端到端的负荷预测模型，能够有效应对缺失数据。 • 引入基于掩码的时序降采样及分层空间粗化-细化方法。 • 在真实负荷数据上，当缺失率达到90%时，模型误差最多可降低17.4%。

期刊

Applied Energy

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论文数:

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被引数:

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university of electronic science and technology of china

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aalborg university

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