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Data-driven models for predicting compressive strength of 3D-printed fiber-reinforced concrete using interpretable machine learning algorithms

Crossref DOI link: https://doi.org/10.1016/j.cscm.2024.e03935

Published Print: 2024-12

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Arif, Muhammad

Jan, Faizullah

Rezzoug, Aïssa

Afridi, Muhammad Ali

Luqman, Muhammad

Khan, Waseem Akhtar

Kujawa, Marcin

Alabduljabbar, Hisham

Khan, Majid
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Text and Data Mining valid from 2024-12-01

Text and Data Mining valid from 2024-12-01

Version of Record valid from 2024-10-30
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This article is maintained by: Elsevier

Article Title: Data-driven models for predicting compressive strength of 3D-printed fiber-reinforced concrete using interpretable machine learning algorithms

Journal Title: Case Studies in Construction Materials

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.cscm.2024.e03935

Content Type: article

Copyright: © 2024 The Author(s). Published by Elsevier Ltd.