Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches

To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of fly-ash concrete using a comparative study of machine learning techniques, namely random forest regression (RFR) and gene expression programming...

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