Song Yu*, Aiping Luo, Xiang Wang
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1877-1893, 2023, DOI:10.32604/iasc.2023.039132
Abstract Railway passenger flow forecasting can help to develop sensible railway schedules, make full use of railway resources, and meet the travel demand of passengers. The structure of passenger flow in railway networks and the spatiotemporal relationship of passenger flow among stations are two distinctive features of railway passenger flow. Most of the previous studies used only a single feature for prediction and lacked correlations, resulting in suboptimal performance. To address the above-mentioned problem, we proposed the railway passenger flow prediction model called Flow-Similarity Attention Graph Convolutional Network (F-SAGCN). First, we constructed the passenger flow relations… More >
Login
Register
