Retraction Note: A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults.

Djaballah S, Saidi L, Meftah K, Hechifa A, Bajaj M, Zaitsev I

DOI: 10.1038/s41598-026-55815-z
Published: 2026 Jun 8
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-55815-z,
  title = {Retraction Note: A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults.},
  author = {Djaballah S and Saidi L and Meftah K and Hechifa A and Bajaj M and Zaitsev I},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-55815-z},
  url = {https://doi.org/10.1038/s41598-026-55815-z}
}

RIS

TY  - JOUR
TI  - Retraction Note: A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults.
AU  - Djaballah S
AU  - Saidi L
AU  - Meftah K
AU  - Hechifa A
AU  - Bajaj M
AU  - Zaitsev I
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-55815-z
UR  - https://doi.org/10.1038/s41598-026-55815-z
ER  -

APA

S, D., L, S., K, M., A, H., M, B., & I, Z. (2026). Retraction Note: A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults.. Scientific reports. https://doi.org/10.1038/s41598-026-55815-z

Source records

pubmed · retrieved 2026-09-26T00:22:07.050Z