Syed Farasat Ali Shah, Bing Chen, Muhammad Zahid and Muhammad Riaz Ahmad
Article (2022)
An external link is available for this itemDepartment: | Department of Civil, Geological and Mining Engineering |
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PolyPublie URL: | https://publications.polymtl.ca/53197/ |
Journal Title: | Construction and Building Materials (vol. 360) |
Publisher: | Elsevier sci ltd |
DOI: | 10.1016/j.conbuildmat.2022.129534 |
Official URL: | https://doi.org/10.1016/j.conbuildmat.2022.129534 |
Date Deposited: | 18 Apr 2023 14:59 |
Last Modified: | 25 Sep 2024 16:44 |
Cite in APA 7: | Shah, S. F. A., Chen, B., Zahid, M., & Ahmad, M. R. (2022). Compressive strength prediction of one-part alkali activated material enabled by interpretable machine learning. Construction and Building Materials, 360, 129534 (10 pages). https://doi.org/10.1016/j.conbuildmat.2022.129534 |
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