Metro Traffic Flow Prediction via Knowledge Graph and Spatiotemporal Graph Neural Network

Metro Traffic Flow Prediction via Knowledge Graph and Spatiotemporal Graph Neural Network

Existing traffic flow prediction methods generally only consider the spatiotemporal characteristics of traffic flow. However, in addition to the spatiotemporal characteristics, the interference of various external factors needs to be considered in traffic flow prediction, including severe weather, m...

Full description

Saved in:

Bibliographic Details
Main Authors:	Shun Wang, Yimei Lv, Yuan Peng, Xinglin Piao, Yong Zhang
Format:	Article
Language:	English
Published:	Wiley 2022-01-01
Series:	Journal of Advanced Transportation
Online Access:	http://dx.doi.org/10.1155/2022/2348375
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A spatiotemporal graph wavelet neural network for traffic flow prediction
by: Linjie Zhang, et al.
Published: (2025-03-01)

Urban Traffic Flow Forecasting Based on Graph Structure Learning
by: Guangyu Huo, et al.
Published: (2024-01-01)

Spatiotemporal fusion knowledge tracking model based on spatiotemporal graph and fourier graph neural network
by: Yinquan Liu, et al.
Published: (2025-07-01)

Maritime Traffic Knowledge Discovery via Knowledge Graph Theory
by: Shibo Li, et al.
Published: (2024-12-01)

Linear attention based spatiotemporal multi graph GCN for traffic flow prediction
by: Yanping Zhang, et al.
Published: (2025-03-01)

Encrypted traffic classification method based on parallel traffic graph and graph neural network
by: LIU Taotao, et al.
Published: (2025-06-01)

Dynamic spatiotemporal graph network for traffic accident risk prediction
by: Pengcheng Zhang, et al.
Published: (2025-12-01)

Research on Urban Road Traffic Flow Prediction Based on Sa-Dynamic Graph Convolutional Neural Network
by: Song Hu, et al.
Published: (2025-01-01)

Multi-scale spatio-temporal graph neural network for urban traffic flow prediction
by: Hui Chen, et al.
Published: (2025-07-01)

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting
by: Yang Cao, et al.
Published: (2022-01-01)

An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction
by: Zhiguo Xiao, et al.
Published: (2025-07-01)

Predicting traffic flow with federated learning and graph neural with asynchronous computations network
by: Muhammad Yaqub, et al.
Published: (2025-07-01)

Optimal Graph Information Fused Graph Attention Network for Traffic Flow Forecasting
by: Xing Xu, et al.
Published: (2025-01-01)

Analysis of Traffic Accident Based on Knowledge Graph
by: Liyan Zhang, et al.
Published: (2022-01-01)

STFDSGCN: Spatio-Temporal Fusion Graph Neural Network Based on Dynamic Sparse Graph Convolution GRU for Traffic Flow Forecast
by: Jiahao Chang, et al.
Published: (2025-05-01)

Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction
by: Ariyo Oluwasanmi, et al.
Published: (2023-04-01)

Graph learning-based spatial-temporal graph convolutional neural networks for traffic forecasting
by: Na Hu, et al.
Published: (2022-12-01)

Integrating metro passenger flow data to improve the classification of urban functional regions using a heterogeneous graph neural network
by: Pengxin Zhang, et al.
Published: (2024-12-01)

Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting
by: Xiangyue Zhang, et al.
Published: (2025-07-01)

T-RippleGNN: Predicting traffic flow through ripple propagation with attentive graph neural networks.
by: Anning Ji, et al.
Published: (2025-01-01)

Multisource Data Fusion With Graph Convolutional Neural Networks for Node-Level Traffic Flow Prediction
by: Lei Huang, et al.
Published: (2024-01-01)

Knowledge Graph-Based Enhanced Transformer for Metro Individual Travel Destination Prediction
by: Hainan Chi, et al.
Published: (2022-01-01)

Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting
by: Vandana Singh, et al.
Published: (2024-12-01)

Inverse Fuzzy-Directed Graph With an Application in Traffic Flow Problem
by: R. Keerthana, et al.
Published: (2024-01-01)

CrossGraphNet: a cross-spatiotemporal graph-based method for traffic speed reconstruction using remote sensing vehicle detection
by: Yan Zhang, et al.
Published: (2025-08-01)

A robust encrypted traffic identification scheme based on graph neural network
by: LI Mengxiang, et al.
Published: (2024-06-01)

Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models
by: Vasundhara Acharya, et al.
Published: (2025-08-01)

Dual-Channel Dynamic Gated Spatio-Temporal Graph for Traffic Flow Forecasting
by: Chao Wang, et al.
Published: (2025-01-01)

A dynamic preference recommendation model based on spatiotemporal knowledge graphs
by: Xinyu Fan, et al.
Published: (2024-11-01)

Transductive zero-shot learning via knowledge graph and graph convolutional networks
by: Qiong Li, et al.
Published: (2025-08-01)

Dual Graph for Traffic Forecasting
by: Long Wei, et al.
Published: (2025-01-01)

Graph neural network driven traffic prediction technology:review and challenge
by: Yi ZHOU, et al.
Published: (2021-12-01)

Graph neural network driven traffic prediction technology:review and challenge
by: Yi ZHOU, et al.
Published: (2021-12-01)

Multibranch Adaptive Fusion Graph Convolutional Network for Traffic Flow Prediction
by: Xin Zan, et al.
Published: (2023-01-01)

Frequency Enhanced Dynamic Graph Convolutional Networks for Traffic Flow Forecasting
by: Liyuan Wang, et al.
Published: (2025-01-01)

An edge enhancement graph neural network model with node discrimination for knowledge graph representation learning
by: Tao Wang, et al.
Published: (2025-04-01)

A knowledge graph construction method based on co-occurrence for traffic entity prediction
by: Zhangcai Yin, et al.
Published: (2025-08-01)

Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification
by: Hunmin Lee, et al.
Published: (2025-01-01)

A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks.
by: Shaowei Sun, et al.
Published: (2025-01-01)

An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks
by: Manikandan Rajagopal, et al.
Published: (2025-07-01)