Comprehensive review of machine learning in geotechnical reliability analysis: Algorithms, applications and further challenges

• Published in: Applied soft computing Vol. 136; p. 110066
• Main Authors: Zhang, Wengang, Gu, Xin, Hong, Li, Han, Liang, Wang, Lin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2023
• Subjects: Geotechnical engineering; Machine learning; Reliability analysis; Uncertainty; ANN; CNN; Uncertainty; BF; RLEM; RV; ELM; SLFN; RVM; GPR; Geotechnical engineering; SVM; FS; SVR; BPNN; 2D; LS-SVM; XGBoost; Pf; RBF; Reliability analysis; GA; LSF; ML; AI; CSRSM; PSO; RSM; FEM; 3D; PCE; BCS; RF; MARS; ARVM; ASVM; Machine learning; RFEM; GCV; MCS

Geotechnical reliability analysis provides a novel way to rationally take the underlying geotechnical uncertainties into account and evaluate the stability of geotechnical structures by failure probability (or equivalently, reliability index) from a probabilistic perspective, which has gained great...