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A multiscale-based model for train delay prediction considering spatio-temporal correlations
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DOI：10.1016/j.trc.2025.105417.png)
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Abstract
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• Adaptive multi-scale segmentation module was designed to capture temporal dynamics. • The GA-MTSC framework integrated linear attention and adaptive graph convolution. • MTSC reweights multi-scale outputs to capture nonlinear and periodic patterns. • Experiment with real-world data showed superior performance of the proposed method.
Keywords:
Train delay prediction
Frequency domain
Spatio-temporal correlation
Multi time scales
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