Prediction of The Recycled Aggregate Concrete Compressive Strength Using Novel Machine Learning Model and Metaheuristic Algorithms

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Authors

Publication Details

Journal
International Journal of Critical Infrastructures
Published
2025-02-28
DOI
https://doi.org/10.1504/ijcis.2027.10069677
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
Field-Weighted Citation Impact
0.00
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article

Prediction of The Recycled Aggregate Concrete Compressive Strength Using Novel Machine Learning Model and Metaheuristic Algorithms

Xiu‐Yuan Li, Zhiyong Wang
International Journal of Critical Infrastructures
Recycled Aggregate Concrete Performance
article

Prediction of The Recycled Aggregate Concrete Compressive Strength Using Novel Machine Learning Model and Metaheuristic Algorithms

Xiu‐Yuan Li, Zhiyong Wang
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Critical InfrastructuresVol. 23(1)
Openalex Percentile: Top 97%
Recycled Aggregate Concrete Performance
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Prediction of The Recycled Aggregate Concrete Compressive Strength Using Novel Machine Learning Model and Metaheuristic Algorithms — Xiu‐Yuan Li, Zhiyong Wang · International Journal of Critical Infrastructures (2025) | TGRS Research Map | TGRS