A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compr...
A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Supervised machine learning and its algorithm is an emerging trend for the prediction of mechanical properties of concrete. This study uses an ensemble random forest (RF) and gene expression programming (GEP) algorithm for the compressive strength prediction of high strength concrete. The parameters include cement content, coarse aggregate to fine...
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A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)
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TN_cdi_doaj_primary_oai_doaj_org_article_95c21c7f48fe4e2d8e9d7d9dcd6346f9
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_95c21c7f48fe4e2d8e9d7d9dcd6346f9
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ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app10207330
