---
title: "Urban Traffic Speed Dataset of Guangzhou, China"
description: "3 papers in the tracked journals link to the Zenodo dataset Urban Traffic Speed Dataset of Guangzhou, China in their Crossref records, the first in 2021; most of them (1) in 2024."
url: https://scholar4ai.com/code/zenodo-1205229
markdown_url: https://scholar4ai.com/code/zenodo-1205229.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the Zenodo dataset Urban Traffic Speed Dataset of Guangzhou, China in their Crossref records, the first in 2021; most of them (1) in 2024. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# Urban Traffic Speed Dataset of Guangzhou, China: papers linking to it

Research papers in the 480 tracked journals that link to Urban Traffic Speed Dataset of Guangzhou, China (https://doi.org/10.5281/zenodo.1205229), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- Zenodo
- Dataset
- 2018
- https://doi.org/10.5281/zenodo.1205229

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the Zenodo dataset Urban Traffic Speed Dataset of Guangzhou, China in their Crossref records, the first in 2021; most of them (1) in 2024.
- By category: AI (3); the journals with the most are Applied Intelligence (1), Information Fusion (1) and Machine Learning (1).

## By year

*Papers linking to Urban Traffic Speed Dataset of Guangzhou, China by publication year*

| Year | Papers |
|---|---:|
| 2021 | 1 |
| 2023 | 1 |
| 2024 | 1 |

## Journals

*Journals whose papers link to Urban Traffic Speed Dataset of Guangzhou, China most*

| Journal | Papers |
|---|---:|
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 1 |
| [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 1 |

## Papers

*Papers linking to Urban Traffic Speed Dataset of Guangzhou, China, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2023-11-04 | [ADCT-Net: Adaptive traffic forecasting neural network via dual-graphic cross-fused transformer](https://doi.org/10.1016/j.inffus.2023.102122) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | Jianlei Kong, Xiaomeng Fan, Min Zuo et al. | 96 | cites it |
| 2021-04-28 | [Misalignment problem in matrix decomposition with missing values](https://doi.org/10.1007/s10994-021-05985-w) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Sofia Fernandes, Mário Antunes, Diogo Gomes et al. | 6 | cites it |
| 2024-11-23 | [ST-NAMN: a spatial-temporal nonlinear auto-regressive multichannel neural network for traffic prediction](https://doi.org/10.1007/s10489-024-06055-z) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Jiankai Zuo, Yaying Zhang | 2 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). Urban Traffic Speed Dataset of Guangzhou, China: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/zenodo-1205229

```bibtex
@misc{scholar4ai-code-zenodo-1205229,
  author = {{Scholar4AI}},
  title = {Urban Traffic Speed Dataset of Guangzhou, China: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/zenodo-1205229}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).