An integrated dynamic-evaluation and multi-task deep learning framework for load forecasting and compressor scheduling in nonlinear industrial air systems.
- DOI
- 10.1038/s41598-026-61315-x
- Published
- 2026 Jul 12
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-61315-x,
title = {An integrated dynamic-evaluation and multi-task deep learning framework for load forecasting and compressor scheduling in nonlinear industrial air systems.},
author = {Wang Z and Wu N and Meng X and Shao S},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-61315-x},
url = {https://doi.org/10.1038/s41598-026-61315-x}
}RIS
TY - JOUR TI - An integrated dynamic-evaluation and multi-task deep learning framework for load forecasting and compressor scheduling in nonlinear industrial air systems. AU - Wang Z AU - Wu N AU - Meng X AU - Shao S PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-61315-x UR - https://doi.org/10.1038/s41598-026-61315-x ER -
APA
Z, W., N, W., X, M., & S, S. (2026). An integrated dynamic-evaluation and multi-task deep learning framework for load forecasting and compressor scheduling in nonlinear industrial air systems.. Scientific reports. https://doi.org/10.1038/s41598-026-61315-x
Source records
- pubmed · retrieved 2026-09-25T13:55:56.267Z