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Multi-scale persistent spatiotemporal transformer for long-term urban traffic flow prediction

Jia-Jun Zhong Yong Ma Xin-Zheng Niu Philippe Fournier-Viger Bing Wang Zu-kuan Wei

电子科技学刊2024，Vol.22Issue(1)：53-69,17.
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电子科技学刊2024，Vol.22Issue(1)：53-69,17.DOI:10.1016/j.jnlest.2024.100244

Multi-scale persistent spatiotemporal transformer for long-term urban traffic flow prediction

Multi-scale persistent spatiotemporal transformer for long-term urban traffic flow prediction

Jia-Jun Zhong 1Yong Ma 1Xin-Zheng Niu 1Philippe Fournier-Viger 2Bing Wang 3Zu-kuan Wei1

作者信息

  • 1. School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu,611731,China
  • 2. College of Computer Science&Software Engineering,Shenzhen University,Shenzhen,518060,China
  • 3. School of Computer Science,Southwest Petroleum University,Chengdu,610500,China
  • 折叠

摘要

关键词

Graph neural network/Multi-head attention mechanism/Spatio-temporal dependency/Traffic flow prediction

Key words

Graph neural network/Multi-head attention mechanism/Spatio-temporal dependency/Traffic flow prediction

引用本文复制引用

Jia-Jun Zhong,Yong Ma,Xin-Zheng Niu,Philippe Fournier-Viger,Bing Wang,Zu-kuan Wei..Multi-scale persistent spatiotemporal transformer for long-term urban traffic flow prediction[J].电子科技学刊,2024,22(1):53-69,17.

基金项目

This work is supported by the National Natural Science Foundation of China under Grant No.62272087 （）

Science and Technology Planning Project of Sichuan Province under Grant No.2023YFG0161. （）

电子科技学刊

1674-862X

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