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This paper benchmarks six generative deep learning models for nowcasting aerosol particle size distributions from PM2.5 and meteorological data, finding that physics-guided flow matching performs best, with a reduced general dynamic equation constraint lowering CRPS by 5.5–11.5% at the training site.
该论文提出 GCRN+(图卷积循环网络),利用稀疏固定传感器(仅覆盖 15.6% 路段)结合历史探针车数据监督,在达拉斯-沃思堡高速网络上实现全网当前及未来一小时车速的估计与预测,性能显著优于历史均值及 STID、STAEformer 等基线模型。