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20162020
most citedForecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency

52 citations · 82 across the 3 of their papers we have counts for

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cs.LG2020★ 52 cited

Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency

Xinglei Wang, Xuefeng Guan, Jun Cao +2

Obtaining accurate information about future traffic flows of all links in a traffic network is of great importance for traffic management and control applications. This research st…