MGC-GAN: Multi-Graph Convolutional Generative Adversarial Networks for Accurate Citywide Traffic Flow Prediction

Li, L; Bi, J; Yang, K; Luo, F; Yang, Luxing

MGC-GAN: Multi-Graph Convolutional Generative Adversarial Networks for Accurate Citywide Traffic Flow Prediction

conference contribution

posted on 2023-02-21, 01:47 authored by L Li, J Bi, K Yang, F Luo, Luxing YangLuxing Yang

MGC-GAN: Multi-Graph Convolutional Generative Adversarial Networks for Accurate Citywide Traffic Flow Prediction

History

Volume

2022-October

Pagination

2557-2562

Location

Prague, Czech Republic

Publisher DOI

https://doi.org/10.1109/SMC53654.2022.9945489

Start date

2022-10-09

End date

2022-10-12

ISSN

1062-922X

ISBN-13

9781665452588

Language

English

Publication classification

E1 Full written paper - refereed

Title of proceedings

SMC 2022 : Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2022

Event

IEEE International Conference on Systems, Man, and Cybernetics. (2022 : Prague, Czech Republic)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Publication URL

http://dx.doi.org/10.1109/smc53654.2022.9945489

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Keywords

citywide mobility prediction spatial-temporal analysis and understanding graph convolutional networks adversarial learning

MGC-GAN: Multi-Graph Convolutional Generative Adversarial Networks for Accurate Citywide Traffic Flow Prediction

History

Volume

Pagination

Location

Publisher DOI

Start date

End date

ISSN

ISBN-13

Language

Publication classification

Title of proceedings

Event

Publisher

Place of publication

Publication URL

Usage metrics

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Keywords

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