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Integrating advanced data imputation techniques and machine learning models to develop a predictive model for compressive strength of geopolymer concrete

Crossref DOI link: https://doi.org/10.1007/s43452-025-01254-y

Published Online: 2025-06-27

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Rathnayaka, Madushan

Wijesundara, Kushan

Gunasekara, Chamila https://orcid.org/0000-0003-2013-8720
Law, David W.

Karunasingha, Dulakshi

Lokuge, Weena
Funding

Funding for this research was provided by:

Royal Melbourne Institute of Technology
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Text and Data Mining valid from 2025-06-27

Version of Record valid from 2025-06-27
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Article History

Received: 13 January 2025

Revised: 7 June 2025

Accepted: 14 June 2025

First Online: 27 June 2025

Declarations

:

: The authors declare that they have no known conflict financial interest or personal relationships that could have appeared to influence the work reported in the paper.

: Not applicable.

: As a corresponding author or on behalf of all authors of the research paper, I consent to participate.

: All author of the research paper is consent to the publication. This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.

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