Tribological Properties Assessment of Metallic Glasses Through a Genetic Algorithm-Optimized Machine Learning Model-Reference-Cited by-同舟云学术

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Tribological Properties Assessment of Metallic Glasses Through a Genetic Algorithm-Optimized Machine Learning Model

Published:2023-10-14 Issue: Volume: Page:
ISSN:1598-9623
Container-title:Metals and Materials International
language:en
Short-container-title:Met. Mater. Int.

Author:

Rahardja Untung,Sari Arif,Alsalamy Ali H.,Askar Shavan,Alawadi Ahmed Hussien Radie,Abdullaeva Barno

Publisher

Springer Science and Business Media LLC

Subject

Materials Chemistry,Metals and Alloys,Mechanics of Materials,Condensed Matter Physics

Link

https://link.springer.com/content/pdf/10.1007/s12540-023-01538-z.pdf

Reference72 articles.

1. S. Zhang, Z. Zhang, P. He, Z. Hu, Z. Jing, Y. Gao, X. Liang, J. Non. Cryst. Solids 576, 121268 (2022)

2. R. Sheng, Z. An, A.C.-P. Chuang, X. Xie, P.K. Liaw, Y. Tong, Scr. Mater. 223, 115062 (2023)

3. F. Sun, S. Deng, J. Fu, J. Zhu, D. Liang, P. Wang, H. Zhao, F. Gong, J. Ma, Y. Liu, J. Mater. Sci. Technol. 158, 121 (2023)

4. Y.J. Kim, J.S. Kim, W.C. Kim, J.W. Park, W.T. Kim, D.H. Kim, Met. Mater. Int. 28, 1053 (2022)

5. M. Mohri, M.R. Chellali, D. Wang, J. Ivanisenko, Met. Mater. Int. 28, 1650 (2022)

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