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Interpretable machine learning for predicting the strength of 3D printed fiber-reinforced concrete (3DP-FRC)

Crossref DOI link: https://doi.org/10.1016/j.jobe.2023.106648

Published Print: 2023-08

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Authors

Uddin, Md Nasir

Ye, Junhong

Deng, Boyu https://orcid.org/0000-0003-4733-4596
Li, Ling-zhi https://orcid.org/0000-0002-9477-6824
Yu, Kequan https://orcid.org/0000-0002-8396-4213
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (52108243)

Natural Science Foundation of Chongqing (2022NSCQ-MSX5639)

Fundamental Research Funds for the Central Universities
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This article is maintained by: Elsevier

Article Title: Interpretable machine learning for predicting the strength of 3D printed fiber-reinforced concrete (3DP-FRC)

Journal Title: Journal of Building Engineering

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jobe.2023.106648

Content Type: article

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