An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction.
- DOI
- 10.1038/s41598-026-56169-2
- Published
- 2026 Jun 17
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-56169-2,
title = {An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction.},
author = {Shabrawy M and El-Kenawy EM and Abdel-Hamid NB and Abdelsalam MM},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-56169-2},
url = {https://doi.org/10.1038/s41598-026-56169-2}
}RIS
TY - JOUR TI - An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction. AU - Shabrawy M AU - El-Kenawy EM AU - Abdel-Hamid NB AU - Abdelsalam MM PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-56169-2 UR - https://doi.org/10.1038/s41598-026-56169-2 ER -
APA
M, S., EM, E., NB, A., & MM, A. (2026). An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction.. Scientific reports. https://doi.org/10.1038/s41598-026-56169-2
Source records
- pubmed · retrieved 2026-09-25T23:50:33.872Z