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A Bending Test for Determining the Atterberg Plastic Limit in Soils
Published on: June 28, 2016
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Soft computing models for prediction of bentonite plastic concrete strength
Waleed Bin Inqiad1, Muhammad Faisal Javed2,3, Kennedy Onyelowe4,5
1Military College of Engineering (MCE), National University of Science and Technology (NUST), Islamabad, 44000, Pakistan.
Scientific Reports
|August 5, 2024
Summary
This study introduces advanced algorithms like AdaBoost, MEP, and GEP to predict bentonite plastic concrete strength. AdaBoost achieved the highest accuracy, identifying key factors for practical civil engineering applications.
Area of Science:
- Civil Engineering
- Materials Science
- Computational Intelligence
Background:
- Bentonite plastic concrete (BPC) is crucial for watertight structures due to its plasticity and workability.
- Bentonite in concrete aids in toxic metal adsorption.
- Accurate strength prediction is vital for BPC's modified designs.
Purpose of the Study:
- To apply multi-expression programming (MEP), gene expression programming (GEP), and AdaBoost for predicting BPC's 28-day compressive strength.
- To develop reliable predictive models based on BPC mixture composition.
- To compare the performance of evolutionary and boosting algorithms in strength prediction.
Main Methods:
- Trained MEP, GEP, and AdaBoost models on a dataset of 246 BPC mixtures.
- Utilized six key input factors for strength prediction.
- Evaluated model performance using correlation coefficient (R) and root mean square error (RMSE).
Main Results:
- All models achieved R > 0.9 for training and testing.
- AdaBoost demonstrated superior accuracy with a testing RMSE of 1.66, outperforming MEP (2.02) and GEP (2.38).
- Shapley analysis identified cement, coarse aggregate, and fine aggregate as critical predictors.
Conclusions:
- AdaBoost is a highly effective tool for predicting BPC compressive strength.
- Developed empirical equations via MEP and GEP, but AdaBoost offered superior predictive performance.
- An interactive GUI was created for practical industry use in BPC strength prediction.
Keywords:
AdaBoostBentoniteCompressive strengthGenetic programmingPlastic concreteShapley additive explanationMore Related Videos
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