Application of machine learning models for the compressive strength prediction of concrete with glass waste powder-Reference-Cited by-同舟云学术

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Application of machine learning models for the compressive strength prediction of concrete with glass waste powder

Published:2024 Issue: Volume: Page:123-149
ISSN:
Container-title:Artificial Intelligence Applications for Sustainable Construction
language:en
Short-container-title:

Author:

Kovačević Miljan,Grubeša Ivanka Netinger,Hadzima-Nyarko Marijana,Nyarko Emmanuel Karlo^ORCID

Publisher

Elsevier

Reference34 articles.

1. Modeling the compressive strength of concrete containing waste glass using multi-objective automatic regression;Golafshani;Neural Computing and Applications,2022

2. Waste glass in cement and geopolymer concretes: a review on durability and challenges;Siddika;Polymers,2021

3. Recycling of waste glass as aggregate in cement-based materials;Harrison;Environmental Science and Ecotechnology,2020

4. Effect of waste glass addition as a replacement for fine aggregate on properties of mortar;Malek;Materials,2020

5. Concrete containing waste glass as an environmentally friendly aggregate: a review on fresh and mechanical characteristics;Qaidi;Materials,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete;Engineering Applications of Artificial Intelligence;2024-08

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