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IJSTR >> Volume 9 - Issue 4, April 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Estimation Of Compressive Strength Of Concrete Containing Manufactured Sand By Random Forest

[Full Text]

 

AUTHOR(S)

Hai-Bang Ly, Van Quan Tran

 

KEYWORDS

manufactured sand, concrete, compressive strength, random forest, machine learning

 

ABSTRACT

The compressive strength of concrete is an important parameter that required a precise manner to forecast before any fabrication process to save time and cost. In this work, the possibility of using Random Forest, as a machine learning algorithm, to predict the compressive strength of manufactured sand concrete was investigated. A reliable dataset containing experimental results from the available literature was collected and used to construct and validate the RF black-box. The results of this study encouraged the use RF to predict the compressive strength of concrete containing manufactured sand, as the correlation between the actual and predicted data was 0.966. Moreover, the curing age and the water to binder ratio were found as the most affecting factors to the prediction process of RF. This study might provide a reliable and quick numerical tool for engineers as to avoid worthless experiments.

 

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