Inland river vessel traffic flow prediction based on environment knowledge embedding and spatial-temporal information extraction

Author:

Huang Chen1,Chen Deshan1,Fan Tengze1,Wu Bing1

Affiliation:

1. Wuhan University of Technology,State Key Laboratory of Maritime Technology and Safety,Wuhan,China

Funder

Nature

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Reference18 articles.

1. Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network

2. Forecasting road traffic speeds by considering area-wide spatio-temporal dependencies based on a graph convolutional neural network (GCN);by;Transportation Research Part C Emerging Technologies,2020

3. Knowledge representation learning with entities, attributes and relations;lin;Twenty-Fifth International Joint Conference on Artificial Intelligence,2016

4. Translating embeddings for modeling multi-relational data;bordes;Proceedings of the 26th International Conference on Neural Information Processing Systems,2013

5. T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction

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