Spatio-Temporal Graph Convolutional Networks: A Deep ...
Spatio-Temporal Graph Convolutional Networks: A Deep learning Frameworkfor Traffic ForecastingBing Yu 1, Haoteng Yin 2,3, Zhanxing Zhu 3,41School of Mathematical Sciences, Peking University, Beijing, China2Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China3Center for Data Science, Peking University, Beijing, China4Beijing Institute of Big Data Research (BIBDR), Beijing, China{byu, htyin, accurate traffic forecast is crucial for ur-ban traffic control and guidance. Due to the highnonlinearity and complexity of traffic flow, tradi-tional methods cannot satisfy the requirements ofmid-and-long term prediction tasks and often ne-glect spatial and temporal dependencies. In this pa-per, we propose a novel deep learning framework, Spatio-Temporal Graph Convolutional Networks(STGCN), to tackle the time series prediction prob-lem in traffic domain.}
1 Introduction Transportation plays a vital role in everybodyÕs daily life. Ac- ... learning layers, to model spatial and temporal dependencies. To the best of our knowledge, it is the Þrst time that to ap- ... The details of each module are described as follows.
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