GATC and DeepCut: Deep spatiotemporal feature extraction and clustering for large-scale transportation network partition-Reference-Cited by-同舟云学术

GATC and DeepCut: Deep spatiotemporal feature extraction and clustering for large-scale transportation network partition

Published:2022-11 Issue: Volume:606 Page:128110
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Zhang Yuan^ORCID,Li Lu,Zhang Wenbo,Cheng Qixiu^ORCID

Funder

National Natural Science Foundation of China

Hong Kong Polytechnic University

Publisher

Elsevier BV

Subject

Statistical and Nonlinear Physics,Statistics and Probability

Reference64 articles.

1. Traffic zone division based on big data from mobile phone base stations;Dong;Transp. Res. C,2015

2. A decomposition approach to the static traffic assignment problem;Jafari;Transp. Res. B,2017

3. A meso-to-macro cross-resolution performance approach for connecting polynomial arrival queue model to volume-delay function with inflow demand-to-capacity ratio;Zhou;Multimodal Transp.,2022

4. Estimation of urban network capacity with second-best constraints for multimodal transport systems;Liu;Transp. Res. B,2021

5. V.L. Knoop, S. Hoogendoorn, J.V. Lint, Impact of traffic dynamics on macroscopic fundamental diagram, in: 92nd Transportation Research Board Meeting, 2013.

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A hybrid deep learning model for urban expressway lane-level mixed traffic flow prediction;Engineering Applications of Artificial Intelligence;2024-07

2. An Adaptive Semantic Mining Framework for Heterogeneous Information Network Embedding;IEEE Transactions on Computational Social Systems;2024-02

3. An ADMM-based parallel algorithm for solving traffic assignment problem with elastic demand;Communications in Transportation Research;2023-12

4. Unsupervised Community Discovery Algorithm via Reconstructed Graph Neural NEtwork;2023 International Conference on Machine Learning and Cybernetics (ICMLC);2023-07-09

5. Full-scale spatio-temporal traffic flow estimation for city-wide networks: a transfer learning based approach;Transportmetrica B: Transport Dynamics;2022-11-10