About this document
Machine Learning for Soil Strength Prediction by meharsai1 is a document available to read on EtoBox.
This study evaluates the effectiveness of various machine learning models, including stand-alone, tree-ensemble, and meta-ensemble algorithms, in predicting the strength of soils improved by partial substitution of Ordinary Portland Cement (OPC) with by-products like PFA and GGBS. Results indicate that ensemble models outperform stand-alone models in accuracy, with the meta-ensemble models showing the highest predictive performance. The study emphasizes the importance of using multiple cross-validation meth
- Author
- meharsai1
- Language
- EN