ACTFormer: Adaptive Complexity-Aware Traffic Transformer for Intelligent Flow Prediction
- DOI
- 10.1109/tnnls.2026.3691371
- Published
- 2026
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3691371,
title = {ACTFormer: Adaptive Complexity-Aware Traffic Transformer for Intelligent Flow Prediction},
author = {Wenbiao Yang and Wenli Shang and Zhiquan Liu},
year = {2026},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2026.3691371},
url = {https://doi.org/10.1109/tnnls.2026.3691371}
}RIS
TY - JOUR TI - ACTFormer: Adaptive Complexity-Aware Traffic Transformer for Intelligent Flow Prediction AU - Wenbiao Yang AU - Wenli Shang AU - Zhiquan Liu PY - 2026 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2026.3691371 UR - https://doi.org/10.1109/tnnls.2026.3691371 ER -
APA
Yang, W., Shang, W., & Liu, Z. (2026). ACTFormer: Adaptive Complexity-Aware Traffic Transformer for Intelligent Flow Prediction. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2026.3691371
Source records
- crossref · retrieved 2026-09-26T16:15:22.880Z