Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.

Guo J, Shen Y

DOI: 10.1155/2022/8568917
Published: 2022
Container: Computational intelligence and neuroscience
Publisher: Not recorded
Open access: yes

Credibility signals

serious concern Score 10/100 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. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
serious concernRetraction Watch retraction: 1 retraction notice matched this DOI. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1155/2022/8568917,
  title = {Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.},
  author = {Guo J and Shen Y},
  year = {2022},
  journal = {Computational intelligence and neuroscience},
  doi = {10.1155/2022/8568917},
  url = {https://doi.org/10.1155/2022/8568917}
}

RIS

TY  - JOUR
TI  - Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.
AU  - Guo J
AU  - Shen Y
PY  - 2022
JO  - Computational intelligence and neuroscience
DO  - 10.1155/2022/8568917
UR  - https://doi.org/10.1155/2022/8568917
ER  -

APA

J, G., & Y, S. (2022). Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.. Computational intelligence and neuroscience. https://doi.org/10.1155/2022/8568917

Source records

pubmed · retrieved 2026-09-24T23:30:09.486Z