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Updated: Jul 22, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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解决更高阶关系和异质性:用于空间时空活动预测的动态异质超图网络

Changyuan Tian1, Zequn Zhang2, Fanglong Yao2

  • 1Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China; Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100190, China.

Neural networks : the official journal of the International Neural Network Society
|July 22, 2023
PubMed
概括

这项研究介绍了DyH2N,这是一种用于空间时空活动预测的新型动态异质超图网络. 它有效地模拟复杂的用户活动模式,优于现有方法.

关键词:
超图形神经网络的神经网络.超图结构学习学习的超图结构.设置表示学习学习的集合表示.时间空间活动预测预测.

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