Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil

Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil

Abstract 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 u...

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Bibliographic Details
Main Authors: Gamil M. S. Abdullah, Mahmood Ahmad, Muhammad Babur, Muhammad Usman Badshah, Ramez A. Al-Mansob, Yaser Gamil, Muhammad Fawad
Format: Article
Language:English
Published: Nature Portfolio 2024-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-52825-7

Internet

https://doi.org/10.1038/s41598-024-52825-7

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