Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms
- DOI
- 10.1007/s40544-023-0847-2
- Published
- 2024-04-02
- Container
- Friction
- Publisher
- Tsinghua University Press
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s40544-023-0847-2,
title = {Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms},
author = {Huifeng Ning and Faqiang Chen and Yunfeng Su and Hongbin Li and Hengzhong Fan and Junjie Song and Yongsheng Zhang and Litian Hu},
year = {2024},
journal = {Friction},
doi = {10.1007/s40544-023-0847-2},
url = {https://doi.org/10.1007/s40544-023-0847-2}
}RIS
TY - JOUR TI - Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms AU - Huifeng Ning AU - Faqiang Chen AU - Yunfeng Su AU - Hongbin Li AU - Hengzhong Fan AU - Junjie Song AU - Yongsheng Zhang AU - Litian Hu PY - 2024 JO - Friction DO - 10.1007/s40544-023-0847-2 UR - https://doi.org/10.1007/s40544-023-0847-2 ER -
APA
Ning, H., Chen, F., Su, Y., Li, H., Fan, H., Song, J., Zhang, Y., & Hu, L. (2024). Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms. Friction. https://doi.org/10.1007/s40544-023-0847-2
Source records
- crossref · retrieved 2026-09-25T18:10:21.050Z