Boosting-based ensemble machine learning models for predicting unconfined compressive strength of ge...
Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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The present research employs new boosting-based ensemble machine learning models i.e., gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined compressive strength (UCS) of geopolymer stabilized clayey soil. The GB and AdaBoost models were developed and validated using 270 clayey soil samples stabilized with geopolymer, wi...
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Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil
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TN_cdi_doaj_primary_oai_doaj_org_article_d78bb0e95ed444babf9e9326590c4d73
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d78bb0e95ed444babf9e9326590c4d73
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-52825-7
