Enhancing Sealing Performance Predictions: A Comprehensive Study of XGBoost and Polynomial Regression Models with Advanced Optimization Techniques.
- DOI
- 10.3390/ma18102392
- Published
- 2025 May 20
- Container
- Materials (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/ma18102392,
title = {Enhancing Sealing Performance Predictions: A Comprehensive Study of XGBoost and Polynomial Regression Models with Advanced Optimization Techniques.},
author = {Zhou W and Xie Z},
year = {2025},
journal = {Materials (Basel, Switzerland)},
doi = {10.3390/ma18102392},
url = {https://doi.org/10.3390/ma18102392}
}RIS
TY - JOUR TI - Enhancing Sealing Performance Predictions: A Comprehensive Study of XGBoost and Polynomial Regression Models with Advanced Optimization Techniques. AU - Zhou W AU - Xie Z PY - 2025 JO - Materials (Basel, Switzerland) DO - 10.3390/ma18102392 UR - https://doi.org/10.3390/ma18102392 ER -
APA
W, Z., & Z, X. (2025). Enhancing Sealing Performance Predictions: A Comprehensive Study of XGBoost and Polynomial Regression Models with Advanced Optimization Techniques.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma18102392
Source records
- pubmed · retrieved 2026-09-27T14:15:47.718Z
- europe-pmc · retrieved 2026-09-27T14:15:47.732Z