Leveraging advanced ensemble learning techniques for methane uptake prediction in metal organic frameworks.
- DOI
- 10.1038/s41598-025-17028-8
- Published
- 2025 Aug 29
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-17028-8,
title = {Leveraging advanced ensemble learning techniques for methane uptake prediction in metal organic frameworks.},
author = {Larestani A and Amiri-Ramsheh B and Atashrouz S and Abedi A and Mohaddespour A and Hemmati-Sarapardeh A},
year = {2025},
journal = {Scientific reports},
doi = {10.1038/s41598-025-17028-8},
url = {https://doi.org/10.1038/s41598-025-17028-8}
}RIS
TY - JOUR TI - Leveraging advanced ensemble learning techniques for methane uptake prediction in metal organic frameworks. AU - Larestani A AU - Amiri-Ramsheh B AU - Atashrouz S AU - Abedi A AU - Mohaddespour A AU - Hemmati-Sarapardeh A PY - 2025 JO - Scientific reports DO - 10.1038/s41598-025-17028-8 UR - https://doi.org/10.1038/s41598-025-17028-8 ER -
APA
A, L., B, A., S, A., A, A., A, M., & A, H. (2025). Leveraging advanced ensemble learning techniques for methane uptake prediction in metal organic frameworks.. Scientific reports. https://doi.org/10.1038/s41598-025-17028-8
Source records
- pubmed · retrieved 2026-09-27T01:27:11.129Z