Open access
Jul 2026
Quantitative prediction of differential settlement based on machine learning techniques.
A data-driven machine learning framework to accurately predict differential settlement at the junction of existing and new embankments is developed, offering a tool for rapid performance prediction and damage assessment that significantly outperforms conventional simulation-based methods in speed and efficiency.
Shaista Jabeen Abbasi, Hu Minqjie, Xiaolin Weng et al.
· Scientific Reports · 0 citations