Metro Passenger Flow Prediction via Dynamic Hypergraph Convolution Networks

IEEE Transactions on Intelligent Transportation Systems(2021)

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摘要
Metro passenger flow prediction is a strategically necessary demand in an intelligent transportation system to alleviate traffic pressure, coordinate operation schedules, and plan future constructions. Graph-based neural networks have been widely used in traffic flow prediction problems. Graph Convolutional Neural Networks (GCN) captures spatial features according to established connections but ig...
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关键词
Predictive models,Public transportation,Convolution,Neural networks,Graph neural networks,Forecasting,Urban areas
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