A hybrid deep learning approach for real-time estimation of passenger traffic flow in urban railway systems

• Main Authors: Fu, Xianlei, Wu, Maozhi, Ponnarasu, Sasthikapreeya, Zhang, Limao
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Civil engineering; Traffic Volume Prediction; Deep Learning
• Online Access: https://hdl.handle.net/10356/171692
• Institution: Nanyang Technological University

This research introduces a hybrid deep learning approach to perform real-time forecasting of passenger traffic flow for the metro railway system (MRS). By integrating long short-term memory (LSTM) and the graph convolutional network (GCN), a hybrid deep learning neural network named the graph convol...