Ruiyuan Jiang

Orcid: 0009-0000-0623-4148

According to our database1, Ruiyuan Jiang authored at least 16 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2026
A joint topology-data fusion graph network for robust traffic speed prediction with data anomalism.
Inf. Sci., 2026

A novel hybrid macroscopic fundamental diagram-informed deep learning method for lane-level traffic prediction.
Inf. Fusion, 2026

2025
New MDS and self-dual generalized Roth-Lempel codes as well as their deep holes.
Des. Codes Cryptogr., November, 2025

A Hierarchical Deep Reinforcement Learning Framework for Traffic Signal Control with Predictable Cycle Planning.
CoRR, September, 2025

Adaptive Vehicle Speed Classification via BMCNN with Reinforcement Learning-Enhanced Acoustic Processing.
CoRR, September, 2025

Integrating Vehicle Acoustic Data for Enhanced Urban Traffic Management: A Study on Speed Classification in Suzhou.
CoRR, June, 2025

An Adaptive Prediction Model for Randomly Distributed Traffic Data in Urban Road Networks.
IEEE Trans. Veh. Technol., May, 2025

Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control.
CoRR, February, 2025

A knowledge-informed dynamic correlation modeling framework for lane-level traffic flow prediction.
Inf. Fusion, 2025

A Survey on RL-Based Approaches for Traffic Signal and Joint Vehicle-Signal Control.
Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

An Adaptive Multi-Source Correlation Fusion Approach for Lane-Level Traffic Flow Prediction.
Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

An Innovative Approach for Vehicle Speed Recognition through Noise Emission Analysis by Using Machine Learning.
Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

2023
A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction.
CoRR, 2023

Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach.
CoRR, 2023

A Joint Traffic Flow Estimation and Prediction Approach for Urban Networks.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023


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