DCENet: A dynamic correlation evolve network for short-term traffic prediction

Shuai Liu, Xiaoyuan Feng, Yilong Ren, Han Jiang and Haiyang Yu

Physica A: Statistical Mechanics and its Applications, 2023, vol. 614, issue C

Abstract: Graph neural networks (GNNs) have been extensively employed in traffic prediction tasks due to their excellent capturing capabilities of spatial dependence. However, the majority of GNN-based approaches tend to employ static graphs, whereas they evolve over time and vary dynamics in real-world traffic situations. It is challenging to capture the dynamic spatial–temporal evolution characteristics of traffic data. To address this problem, we propose a dynamic correlation evolve network (DCENet) for short-term traffic prediction. To be specific, we develop a dynamic correlation self-attention (DCSA) module, which captures dynamic node associations adaptively. In this way, the model acquires new node embedding features without explicitly constructing a new graph structure. Then, an evolution encoder–decoder (EED) module is built to learn the interactions of dynamic features and output future traffic states. The experiments are conducted on two real-world datasets, and the results show that the DCENet outperformers baseline models for most of the cases.

Keywords: Traffic prediction; Dynamic correlations; Self-attention; Encoder–Decoder (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123000808
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:614:y:2023:i:c:s0378437123000808

DOI: 10.1016/j.physa.2023.128525

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().