Machine learning for predicting the half cell potential of cathodically protected reinforced cement concrete slabs subjected to chloride ingress-Reference-Cited by-同舟云学术

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Machine learning for predicting the half cell potential of cathodically protected reinforced cement concrete slabs subjected to chloride ingress

Published:2024-11 Issue: Volume:137 Page:109090
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Murthy Yogesh Iyer^ORCID,Meena Kunj Bihari^ORCID,Patel Nileshkumar^ORCID

Publisher

Elsevier BV

Reference86 articles.

1. Prediction of rapid chloride penetration resistance of metakaolin based high strength concrete using light GBM and XGBoost models by incorporating SHAP analysis;Abdulalim Alabdullah;Construct. Build. Mater.,2022

2. Prediction of compressive strength of concrete incorporated with jujube seed as partial replacement of coarse aggregate: a feasibility of Hammerstein–Wiener model versus support vector machine;Adamu;Model. Earth Syst. Environ.,2021

3. Machine learning applications for developing sustainable construction materials;Adel,2022

4. Application of advanced machine learning approaches to predict the compressive strength of concrete containing supplementary cementitious materials;Ahmad;Materials,2021

5. Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system;Ahmed;Environ. Monit. Assess.,2019

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