Input database and XGBOOST model for Prediction analysis for small-strain stiffness of soil

Published: 19 July 2023| Version 1 | DOI: 10.17632/s3x2vrh3jy.1
Yunhan Huang


This introduction provides an overview of the input database and the XGBOOST model utilized for predicting the small-strain stiffness of soil. The database includes a comprehensive collection of soil samples gathered from various locations across North America and the Pacific Rim over the past four decades. This database is a valuable resource for engineers and researchers seeking to utilize the XGBOOST model for predicting small-strain soil stiffness. To enhance its applicability to various soil types, the database can be expanded by adding more data from other researchers. Additionally, this introduction presents the code for the XGBOOST model with Bayesian Optimization, which includes how the database is partitioned into training and test sets to facilitate the model training. Furthermore, the application of the trained XGBOOST model to a practical case is demonstrated through an example of Toyoura sand.



University of Texas at Austin


Geotechnical Engineering, Civil Engineering