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

• المؤلفون الرئيسيون: Fu, Xianlei, Wu, Maozhi, Ponnarasu, Sasthikapreeya, Zhang, Limao
• مؤلفون آخرون: School of Civil and Environmental Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Civil engineering; Traffic Volume Prediction; Deep Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/171692

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...