Machine Learning-Based Prediction of Stacking Fault Energy in High-Manganese Steels: A Comparative Study of Ensemble and Kernel Methods
- DOI
- 10.3390/ma19101940
- Published
- 2026-05-09
- Container
- Materials
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/ma19101940,
title = {Machine Learning-Based Prediction of Stacking Fault Energy in High-Manganese Steels: A Comparative Study of Ensemble and Kernel Methods},
author = {Saurabh Tiwari and Seong Jun Heo and Nokeun Park},
year = {2026},
journal = {Materials},
doi = {10.3390/ma19101940},
url = {https://doi.org/10.3390/ma19101940}
}RIS
TY - JOUR TI - Machine Learning-Based Prediction of Stacking Fault Energy in High-Manganese Steels: A Comparative Study of Ensemble and Kernel Methods AU - Saurabh Tiwari AU - Seong Jun Heo AU - Nokeun Park PY - 2026 JO - Materials DO - 10.3390/ma19101940 UR - https://doi.org/10.3390/ma19101940 ER -
APA
Tiwari, S., Heo, S. J., & Park, N. (2026). Machine Learning-Based Prediction of Stacking Fault Energy in High-Manganese Steels: A Comparative Study of Ensemble and Kernel Methods. Materials. https://doi.org/10.3390/ma19101940
Source records
- crossref · retrieved 2026-11-10T08:15:28.785Z