A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture.

Shi B, Gao Z, Pu T, Jiang J, Sun Y

Open source

DOI
10.1038/s41598-025-14748-9
Published
2025 Aug 14
Container
Scientific reports
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1038/s41598-025-14748-9,
  title = {A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture.},
  author = {Shi B and Gao Z and Pu T and Jiang J and Sun Y},
  year = {2025},
  journal = {Scientific reports},
  doi = {10.1038/s41598-025-14748-9},
  url = {https://doi.org/10.1038/s41598-025-14748-9}
}

RIS

TY  - JOUR
TI  - A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture.
AU  - Shi B
AU  - Gao Z
AU  - Pu T
AU  - Jiang J
AU  - Sun Y
PY  - 2025
JO  - Scientific reports
DO  - 10.1038/s41598-025-14748-9
UR  - https://doi.org/10.1038/s41598-025-14748-9
ER  -

APA

B, S., Z, G., T, P., J, J., & Y, S. (2025). A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture.. Scientific reports. https://doi.org/10.1038/s41598-025-14748-9

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