A multi-objective hybrid algorithm for optimizing neural network architectures in wildlife conservation: a theoretical framework with practical validation.
- DOI
- 10.1038/s41598-025-21539-9
- Published
- 2025 Dec 11
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-21539-9,
title = {A multi-objective hybrid algorithm for optimizing neural network architectures in wildlife conservation: a theoretical framework with practical validation.},
author = {Kaniwa F and Dinakenyane O and Phuthego M},
year = {2025},
journal = {Scientific reports},
doi = {10.1038/s41598-025-21539-9},
url = {https://doi.org/10.1038/s41598-025-21539-9}
}RIS
TY - JOUR TI - A multi-objective hybrid algorithm for optimizing neural network architectures in wildlife conservation: a theoretical framework with practical validation. AU - Kaniwa F AU - Dinakenyane O AU - Phuthego M PY - 2025 JO - Scientific reports DO - 10.1038/s41598-025-21539-9 UR - https://doi.org/10.1038/s41598-025-21539-9 ER -
APA
F, K., O, D., & M, P. (2025). A multi-objective hybrid algorithm for optimizing neural network architectures in wildlife conservation: a theoretical framework with practical validation.. Scientific reports. https://doi.org/10.1038/s41598-025-21539-9