Yuan Jiang

Title: Innovations in Traffic Flow Forecasting by Yuan Jiang

Introduction

Yuan Jiang is a notable inventor based in Nanchang, China. He has made significant contributions to the field of traffic flow forecasting through his innovative methods. His work focuses on utilizing advanced technologies to improve traffic management and forecasting accuracy.

Latest Patents

Yuan Jiang holds a patent for a "Traffic flow forecasting method based on multi-mode dynamic residual graph convolution network." This method involves constructing a relationship matrix and an adaptive matrix to learn the site dependence relationship for historical traffic data of traffic stations. It employs multi-mode dynamic graph convolution to extract traffic characteristics corresponding to different traffic modes. The method integrates graph convolution into a gated cyclic neural network to combine spatial and temporal dependencies of traffic flow. By connecting the network using dynamic residuals, it effectively combines input traffic data with decoding data to achieve accurate forecasting values. The application utilizes two different methods to construct the adjacency matrix, effectively capturing traffic flow characteristics corresponding to different traffic modes and dynamically fusing these characteristics.

Career Highlights

Yuan Jiang is affiliated with East China Jiaotong University, where he contributes to research and development in traffic management systems. His work has garnered attention for its innovative approach to solving complex traffic forecasting challenges.

Collaborations

Yuan Jiang collaborates with esteemed colleagues, including Xiaohui Huang and Yuming Ye, to advance research in traffic flow forecasting and related fields.

Conclusion

Yuan Jiang's innovative methods in traffic flow forecasting represent a significant advancement in the field. His contributions are paving the way for more efficient traffic management solutions.