Machine Learning Prediction Models to Evaluate the Strength of Recycled Aggregate Concrete

Machine Learning Prediction Models to Evaluate the Strength of Recycled Aggregate Concrete

Compressive and flexural strength are the crucial properties of a material. The strength of recycled aggregate concrete (RAC) is comparatively lower than that of natural aggregate concrete. Several factors, including the recycled aggregate replacement ratio, parent concrete strength, water– cement r...

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Bibliographic Details
Main Authors: Ahmad, A. (Author), Ahmad, W. (Author), Khallaf, R. (Author), Mohamed, A.M (Author), Tian, Y. (Author), Usanova, K.I (Author), Yuan, X. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Adaptive boosting
Bending strength
Compressive and flexural strengths
compressive strength
Compressive strength
Concrete aggregates
Cost effective
Cost effectiveness
Decision trees
Error values
Errors
flexural strength
gradient boosting
Gradient boosting
Machine learning
Machine-learning
Mean absolute error
Mean square error
random forest
Random forest modeling
Random forests
recycled aggregate concrete
Recycled aggregate concrete
Recycling
sustainable aggregate
Sustainable aggregate
Water absorption
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