title: Feature Importance Analysis for Compressive Bearing Capacity of HSCM Piles Based on GA-BPNN
abstract: To address the complex pile–soil interaction mechanisms in predicting the compressive bearing capacity of HSCM piles (Helix Stiffened Cement Mixing piles) in marine soft soil regions, this study proposes an intelligent prediction method based on a GA-BPNN (Genetic Algorithm-Optimized Back Propagation Neural Network). A high-quality database comprising 1243 data points was established through finite element numerical simulations. By integrating data preprocessing techniques and the GA-BPNN model,
journal: Buildings