Predicting the Strength Performance of Hydrated-Lime Activated Rice Husk Ash-Treated Soil Using Two Grey-Box Machine Learning Models

Predicting the Strength Performance of Hydrated-Lime Activated Rice Husk Ash-Treated Soil Using Two Grey-Box Machine Learning Models

Geotechnical engineering relies heavily on predicting soil strength to ensure safe and efficient construction projects. This paper presents a study on the accurate prediction of soil strength properties, focusing on hydrated-lime activated rice husk ash (HARHA) treated soil. To achieve precise predi...

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Bibliographic Details
Main Authors: Abolfazl Baghbani, Amin Soltani, Katayoon Kiany, Firas Daghistani
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Geotechnics
Subjects:
hydrated lime
rice husk ash
machine learning
grey-box model
classification and regression trees
genetic programming
Online Access:https://www.mdpi.com/2673-7094/3/3/48

Internet

https://www.mdpi.com/2673-7094/3/3/48

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