Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 10, 2024Applied SciencesOpen Access

Multi-Step Passenger Flow Prediction for Urban Metro System Based on Spatial-Temporal Graph Neural Network

View Full Paper
Ask AI
Bookmark
Share

Authors

YCYuchen ChangMZMengya ZongYDYutian Dang

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Chang et al. (2024) studied this question.

synapsesocial.com/papers/68e58decb6db643587529cebhttps://doi.org/10.3390/app14188121
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A dynamic multigraph and multidimensional attention neural network model for metro passenger flow prediction2024 · 2 citations
  2. 2Origin-destination flow generation for metro network expansion using spatiotemporal gated graph neural networks2026
  3. 3A deep learning and station feature fusion-based architecture for subway passenger flow prediction in intelligent transportation systems2026
  4. 4Disentanglement-Guided Spatial-Temporal Graph Neural Network for Metro Flow Forecasting (Student Abstract)2024
  5. 5A dynamic graph deep learning model with multivariate empirical mode decomposition for network‐wide metro passenger flow prediction2024 · 6 citations