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A reliable hybrid extreme learning machine-metaheuristic framework for enhanced strength prediction of 3D-printed fiber-reinforced concrete

Crossref DOI link: https://doi.org/10.1016/j.rineng.2025.105715

Published Print: 2025-09

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

Authors

Alizamir, Meysam https://orcid.org/0000-0003-1047-1917
Kim, Sungwon

Ikram, Rana Muhammad Adnan

Ahmed, Kaywan Othman

Heddam, Salim

Gholampour, Aliakbar
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (52350410465)

National Natural Science Foundation of China (2023A1515011520)
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Text and Data Mining valid from 2025-09-01

Text and Data Mining valid from 2025-09-01

Version of Record valid from 2025-06-10
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This article is maintained by: Elsevier

Article Title: A reliable hybrid extreme learning machine-metaheuristic framework for enhanced strength prediction of 3D-printed fiber-reinforced concrete

Journal Title: Results in Engineering

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.rineng.2025.105715

Content Type: article

Copyright: © 2025 The Author(s). Published by Elsevier B.V.