Traffic prediction based on spatial-temporal disentangled generative models-Reference-Cited by-同舟云学术

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Traffic prediction based on spatial-temporal disentangled generative models

Published:2024-10 Issue: Volume:680 Page:121142
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Gao Xinyu,Li Hongtao,Zhang Haina,Xue Jiang^ORCID,Sun Shaolong,Liu Wenzheng

Publisher

Elsevier BV

Reference48 articles.

1. A3T-GCN: attention temporal graph convolutional network for traffic forecasting;Bai;ISPRS Int.l J. Geo-Inf.,2021

2. Adaptive graph convolutional recurrent network for traffic forecasting;Bai,2020

3. Spatial–temporal complex graph convolution network for traffic flow prediction;Bao;Eng. Appl. Artif. Intell.,2023

4. A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting;Cai;Transp. Res., Part C, Emerg. Technol.,2016

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