Dynamic traffic network representation model for improving the prediction performance of passenger flow for mass rapid transit

Author:

Wu Jheng-LongORCID,Chung Wei-Yi,Wu Yu-Hsuan,Ho Yen-Nan

Funder

National Science and Technology Council

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Reference49 articles.

1. Modeling multi-regional temporal correlation with gated recurrent unit and multiple linear regression for urban traffic flow prediction;Rajeh;Knowl Based. Syst.,2023

2. A novel hybrid model combining a fuzzy inference system and a deep learning method for short-term traffic flow prediction;Liu;Knowl. Based Syst.,2022

3. Semi-supervised classification with graph convolutional networks;Kipf,2017

4. T-GCN: a temporal graph convolutional network for traffic prediction;Zhao;IEEE Trans. Intell. Transp. Syst.,2019

5. T. Mikolov, K. Chen, G. Corrado, J. Dean, Efficient estimation of word representations in vector space, 2013, arXiv:1301.3781.

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