GCN-GAN: Integrating Graph Convolutional Network and Generative Adversarial Network for Traffic Flow Prediction-Reference-Cited by-同舟云学术

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GCN-GAN: Integrating Graph Convolutional Network and Generative Adversarial Network for Traffic Flow Prediction

Published:2022 Issue: Volume:10 Page:94051-94062
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zheng Hongling¹^ORCID,Li Xiang²,Li Yongfeng³,Yan Ziqin⁴,Li Tinghong⁵

Affiliation:

1. School of Information Science and Engineering, Lanzhou University, Lanzhou, China

2. The Fiftieth Research Institute of China Electronic Technology Group Corporation, Shanghai, Putuo, China

3. School of Cyberspace Security, Xi’an Jiaotong University, Xi’an, China

4. The Silk Road Infoport Company Ltd., Xi’an, China

5. China Mobile Communications Corporation Ltd., Beijing, China

Funder

School of Information Science and Engineering, Lanzhou University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09875268.pdf?arnumber=9875268

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1. A traffic-weather generative adversarial network for traffic flow prediction for road networks under bad weather;Engineering Applications of Artificial Intelligence;2024-11

2. Enhancing TinyML-Based Container Escape Detectors With Systemcall Semantic Association in UAVs Networks;IEEE Internet of Things Journal;2024-06-15

3. A Traffic Flow Data Restoration Method Based on an Auxiliary Discrimination Mechanism-Oriented GAN Model;IEEE Internet of Things Journal;2024-06-15

4. GRAPHITE — Generative Reasoning and Analysis for Predictive Handling in Traffic Efficiency;Information Fusion;2024-06

5. A MACHINE LEARNING APPROACH FOR PREDICTIVE ANALYSIS OF TRAFFIC FLOW;ShodhKosh: Journal of Visual and Performing Arts;2024-05-31

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