Sen Luan

Title: Innovations by Sen Luan in Transportation Network Forecasting

Introduction

Sen Luan is an innovative inventor based in Beijing, China. He has made significant contributions to the field of transportation network forecasting. His work focuses on utilizing advanced neural network structures to improve traffic prediction methods.

Latest Patents

Sen Luan holds a patent for a "Transportation network speed forecasting method using deep capsule networks with nested LSTM models." This application outlines a method that divides the transport network into road links, calculates average speeds for each link, and maps these speeds into a grid system to generate traffic images representing traffic states at various time intervals. The method employs a CapsNet to capture the spatial relationships between road links, with learned patterns represented in vectors. These vectors are then fed into a nested LSTM model to learn temporal relationships and predict future traffic states using a testing dataset. This innovative approach utilizes a new CapsNet neural structure, which is more efficient in handling complex traffic networks compared to traditional CNN models.

Career Highlights

Sen Luan has demonstrated exceptional expertise in the field of deep learning and transportation systems. His work has garnered attention for its potential to enhance traffic management and improve urban mobility.

Collaborations

Sen Luan has collaborated with notable colleagues, including Xiaolei Ma and Yunpeng Wang, to further advance his research and innovations in transportation forecasting.

Conclusion

Sen Luan's contributions to transportation network forecasting through his innovative patent highlight the importance of advanced neural network techniques in addressing complex traffic challenges. His work is paving the way for more efficient traffic management solutions.