A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network

A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network

Abstract Traffic prediction plays an increasingly important role in intelligent transportation systems and smart cities. Both travelers and urban managers rely on accurate traffic information to make decisions about route selection and traffic management. Due to various factors, both human and natur...

Full description

Saved in:

Bibliographic Details
Main Authors:	Ming Jiang, Zhiwei Liu, Yan Xu
Format:	Article
Language:	English
Published:	Springer 2025-01-01
Series:	Complex & Intelligent Systems
Subjects:	Intelligent transportation Traffic prediction Missing data Graph convolutional neural network Neural ordinary differential equation
Online Access:	https://doi.org/10.1007/s40747-024-01768-7
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Comparative Forecasting of Some Key Economic Indicators Using Artificial Neural Networks and Ordinary Differential Equations: A Case Study of the Turkish Economy
by: Bahatdin Daşbaşı, et al.
Published: (2024-12-01)

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

Asymptotic relationships between two higher order ordinary differential equations
by: Takasi Kusano
Published: (1983-01-01)

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

Meta-path convolution based heterogeneous graph neural network algorithm
by: QIN Zhilong, et al.
Published: (2024-03-01)

D-MGDCN-CLSTM: A Traffic Prediction Model Based on Multi-Graph Gated Convolution and Convolutional Long–Short-Term Memory
by: Linliang Zhang, et al.
Published: (2025-01-01)

MGHCN: Multi-graph structures and hypergraph convolutional networks for traffic flow prediction
by: Xuanxuan Fan, et al.
Published: (2025-01-01)

Solvlng Non-Linear First Order Ordinary Differential Equations.
by: Taremwa, Elias
Published: (2024)

Systems of Ordinary Differential Equations with Time Dependent Coefficient Matrix.
by: Twesiime, Gerald
Published: (2024)

On the boundary value problems for ordinary differential equations with isolated singularity
by: Kristina Aldošina, et al.
Published: (2005-12-01)

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

Short-term urban traffic forecasting in smart cities: a dynamic diffusion spatial-temporal graph convolutional network
by: Xiang Yin, et al.
Published: (2025-01-01)

A network traffic classification method based on random forest and improved convolutional neural network
by: Bensheng YUN, et al.
Published: (2023-07-01)

Encrypted traffic classification method based on convolutional neural network
by: Rongna XIE, et al.
Published: (2022-12-01)

Study on traffic scene semantic segmentation method based on convolutional neural network
by: Linhui LI, et al.
Published: (2018-04-01)

Zero-Shot Traffic Identification with Attribute and Graph-Based Representations for Edge Computing
by: Zikui Lu, et al.
Published: (2025-01-01)

sAMDGCN: sLSTM-Attention-Based Multi-Head Dynamic Graph Convolutional Network for Traffic Flow Forecasting
by: Shiyuan Zhang, et al.
Published: (2025-01-01)

A Network Traffic Prediction Model Based on Layered Training Graph Convolutional Network
by: Yulian Li, et al.
Published: (2025-01-01)

An Adaptive Spatio-Temporal Traffic Flow Prediction Using Self-Attention and Multi-Graph Networks
by: Basma Alsehaimi, et al.
Published: (2025-01-01)

Graph Convolutional Network with Neural Collaborative Filtering for Predicting miRNA-Disease Association
by: Jihwan Ha
Published: (2025-01-01)

Identification method for malicious traffic in industrial Internet under new unknown attack scenarios
by: ZENG Fanyi, et al.
Published: (2024-06-01)

Graph Convolution for Large-Scale Graph Node Classification Task Based on Spatial and Frequency Domain Fusion
by: Junwen Lu, et al.
Published: (2025-01-01)

Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos
by: Shadi Jaradat, et al.
Published: (2025-01-01)

Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction
by: Zexi Yang, et al.
Published: (2025-01-01)

Cross-device fault diagnosis method based on graph convolution and multi-sensor fusion
by: SUN Yuanshuai, et al.
Published: (2024-01-01)

Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network
by: Guimei Yin, et al.
Published: (2025-02-01)

Network traffic classification method basing on CNN
by: Yong WANG, et al.
Published: (2018-01-01)

Cloud Computing Resource Scheduling Algorithm Based on Unsampled Collaborative Knowledge Graph Network
by: Haichuan Sun, et al.
Published: (2024-01-01)

Research on the graphical convolution neural network based benefits recommendation system strategy
by: Tao TAO, et al.
Published: (2023-08-01)

A novel graph convolution and frequency domain filtering approach for hyperspectral anomaly detection
by: Yang Ding, et al.
Published: (2025-01-01)

Homology analysis of malware based on graph
by: Bing-lin ZHAO, et al.
Published: (2017-11-01)

Solutions of Systems of " Order Ordinary Differential Equations Using the Combined Laplace Transform-Adomian Decomposition Method.
by: Byamukama, Justus
Published: (2024)

Resource allocation strategy for ultra-dense Internet of things based on graph convolutional neural network
by: HUANG Jie, et al.
Published: (2024-10-01)

Rethinking spatial-temporal contrastive learning for Urban traffic flow forecasting: multi-level augmentation framework
by: Lin Pan, et al.
Published: (2024-12-01)

Graph-Based Feature Crossing to Enhance Recommender Systems
by: Congyu Cai, et al.
Published: (2025-01-01)

Predicting correlation relationships of entities between attack patterns and techniques based on word embedding and graph convolutional network
by: Weicheng QIU, et al.
Published: (2023-08-01)

Vehicle detection based on SqueezeNet convolutional neural network
by: Zefa WEI, et al.
Published: (2020-09-01)

Ordinary Differential Equations /
by: Birkhoff, Garrett, 1911-1996
Published: (1978)

Prediction of the waterborne navigation density based on the multi-feature spatio-temporal graph convolution network
by: Wei DONG, et al.
Published: (2020-09-01)

Unifying spatiotemporal and frequential attention for traffic prediction
by: Qi Guo, et al.
Published: (2025-01-01)