Physics-Topology-Anchored Learning: A Robust and Lightweight Framework for Time-Series Prediction and Anomaly Detection Under Data Scarcity
- DOI
- 10.3390/s26051721
- Published
- 2026-03-09
- Container
- Sensors
- Publisher
- MDPI AG
- 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:10.3390/s26051721,
title = {Physics-Topology-Anchored Learning: A Robust and Lightweight Framework for Time-Series Prediction and Anomaly Detection Under Data Scarcity},
author = {Xuanhao Hua and Weiqi Yin and Libin Wang and Meng Ma and Jianfeng Yuan and Jing Zhang},
year = {2026},
journal = {Sensors},
doi = {10.3390/s26051721},
url = {https://doi.org/10.3390/s26051721}
}RIS
TY - JOUR TI - Physics-Topology-Anchored Learning: A Robust and Lightweight Framework for Time-Series Prediction and Anomaly Detection Under Data Scarcity AU - Xuanhao Hua AU - Weiqi Yin AU - Libin Wang AU - Meng Ma AU - Jianfeng Yuan AU - Jing Zhang PY - 2026 JO - Sensors DO - 10.3390/s26051721 UR - https://doi.org/10.3390/s26051721 ER -
APA
Hua, X., Yin, W., Wang, L., Ma, M., Yuan, J., & Zhang, J. (2026). Physics-Topology-Anchored Learning: A Robust and Lightweight Framework for Time-Series Prediction and Anomaly Detection Under Data Scarcity. Sensors. https://doi.org/10.3390/s26051721
Source records
- crossref · retrieved 2026-09-27T00:39:11.569Z