Deep learning-driven intelligent data anomaly detection and repair technology for power grids

Artificial Intelligence in Mechanical Manufacturing: From Machine Learning to Generative Pre-trained Transformer

Open Access

Fig. 1

Architecture of the proposed TimeMixer++ temporal data repair model integrated with Qwen2. The pipeline combines multi-resolution temporal imaging, trend-seasonal decomposition, and context-aware generation to impute missing values and detect anomalies in power grid time series.

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