A dynamic graph deep learning model with multivariate empirical mode decomposition for network‐wide metro passenger flow prediction
| Author(s): |
Hao Huang
(School of Transportation and Logistics Southwest Jiaotong University Chengdu China)
Jiannan Mao (Department of Civil and Environmental Engineering University of Wisconsin–Madison Wisconsin Madison USA) Leilei Kang (School of Transportation and Logistics Southwest Jiaotong University Chengdu China) Weike Lu (School of Rail Transportation Soochow University Soochow China) Sijia Zhang (School of Transportation and Logistics Southwest Jiaotong University Chengdu China) Lan Liu (School of Transportation and Logistics Southwest Jiaotong University Chengdu China) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Computer-Aided Civil and Infrastructure Engineering, 17 August 2024, n. 17, v. 39 |
| Page(s): | 2596-2618 |
| DOI: | 10.1111/mice.13214 |
- About this
data sheet - Reference-ID
10784694 - Published on:
20/06/2024 - Last updated on:
20/09/2024
Structurae cooperates with
