Use of machine learning models to predict the water penetration depth in concrete-Reference-Cited by-同舟云学术

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Use of machine learning models to predict the water penetration depth in concrete

Published:2024-10 Issue: Volume:95 Page:110107
ISSN:2352-7102
Container-title:Journal of Building Engineering
language:en
Short-container-title:Journal of Building Engineering

Author:

El-Mir Abdulkader^ORCID,El-Zahab Samer^ORCID,Nasr Dana,Semaan Nabil^ORCID,Assaad Joseph^ORCID,El-Hassan Hilal^ORCID

Funder

ADEK

United Arab Emirates University

Publisher

Elsevier BV

Reference68 articles.

1. Environmental, economic and experimental assessment of the valorization of dredged sediment through sand substitution in concrete;Soleimani;Sci. Total Environ.,2023

2. Environmental and economic life cycle assessment of recycled aggregates concrete in the United Arab Emirates;Alzard;Sustain. Times,2021

3. Revamping corrosion damaged reinforced concrete balconies: life cycle assessment and life cycle cost of life-extending repair methods;Wittocx;J. Build. Eng.,2022

4. Towards safer public school buildings in Lebanon: an advocacy for seismic retrofitting initiative;Naja;Int. J. Disaster Risk Reduct.,2014

5. Smart database design for concrete durability analysis - an application in the Hongkong-Zhuhai-Macau bridge;Ma;Cement Concr. Res.,2023

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