Syed Farasat Ali Shah, Bing Chen, Muhammad Zahid and Muhammad Riaz Ahmad
Article (2022)
An external link is available for this item| Department: | Department of Civil, Geological and Mining Engineering |
|---|---|
| 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: | 08 Apr 2025 07:22 |
| 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 |
|---|---|
Statistics
Dimensions
