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Sugar industry waste produced geopolymer concrete and its compressive strength prediction via statistical analysis and artificial intelligence approach

Crossref DOI link: https://doi.org/10.1007/s41062-023-01168-9

Published Online: 2023-06-27

Published Print: 2023-07

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

Authors

Sikder, Ankita

Saha, Purnachandra https://orcid.org/0000-0002-2722-1669
Singha, Partha Sarathi
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Text and Data Mining valid from 2023-06-27

Version of Record valid from 2023-06-27
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Article History

Received: 30 November 2022

Accepted: 18 June 2023

First Online: 27 June 2023

Declarations

:

: The authors declare that they have no conflict of interest.

: For this type of study Ethical approval is not required.

: This article does not contain any studies involving human subjects.

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