May 29, 2022 · This paper provides a dynamic graph representation learning framework for OD demands prediction. In particular, a hierarchical memory updater is first proposed.

To address this problem, this paper provides a dynamic graph representation learning frame- work for OD demands prediction. In particular, a hierarchical memory ...

However, the prediction of origin-destination (OD) demands is still a challenging problem since the number of OD pairs is usually quadratic to the number of ...

@inproceedings{ijcai2022p331, title = {Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction}, author = {Zhang ...

May 29, 2022 · In this paper, we propose a Hierarchical Memory dynamic graph representation learning framework for OD Prediction. (HMOD). First, a hierarchical ...

The code of Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction. 13 stars 2 forks Branches Tags Activity.

Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction · 1 code implementation • 29 May 2022 • Ruixing Zhang, Liangzhe ...

Future values of this score are then predicted through a model using network state characteristics over the larger, region-wide network as input. These ...

Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction · 1 code implementation • 29 May 2022 • Ruixing Zhang, Liangzhe Han ...

Co-authors ; Dynamic graph learning based on hierarchical memory for origin-destination demand prediction. R Zhang, L Han, B Liu, J Zeng, L Sun. arXiv preprint ...