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Predicting the Compressive Strength and the Effective Porosity of Pervious Concrete Using Machine Learning Methods

Crossref DOI link: https://doi.org/10.1007/s12205-022-1918-z

Published Print: 2022-11

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

Authors

Le, Ba-Anh

Vu, Viet-Hung https://orcid.org/0000-0001-6816-6216
Seo, Soo-Yeon https://orcid.org/0000-0003-1995-2872
Tran, Bao-Viet https://orcid.org/0000-0001-9709-5699
Nguyen-Sy, Tuan https://orcid.org/0000-0001-8968-3394
Le, Minh-Cuong

Vu, Thai-Son
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Text and Data Mining valid from 2022-11-01

Text and Data Mining valid from 2022-11-01

Version of Record valid from 2024-08-20
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This article is maintained by: Elsevier

Article Title: Predicting the Compressive Strength and the Effective Porosity of Pervious Concrete Using Machine Learning Methods

Journal Title: KSCE Journal of Civil Engineering

CrossRef DOI link to publisher maintained version: https://doi.org/10.1007/s12205-022-1918-z

Content Type: article

Copyright: Copyright © 2022 © Korean Society of Civil Engineers 2022 published by Elsevier inc. Published by Elsevier Inc.