Gaussian Process-Based Response Surface Method for Slope Reliability Analysis

Autor: Bin Hu, Guo-shao Su, Jianqing Jiang, Yilong Xiao
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Advances in Civil Engineering, Vol 2019 (2019)
Druh dokumentu: article
ISSN: 1687-8086
1687-8094
DOI: 10.1155/2019/9185756
Popis: A new response surface method (RSM) for slope reliability analysis was proposed based on Gaussian process (GP) machine learning technology. The method involves the approximation of limit state function by the trained GP model and estimation of failure probability using the first-order reliability method (FORM). A small amount of training samples were firstly built by the limited equilibrium method for training the GP model. Then, the implicit limit state function of slope was approximated by the trained GP model. Thus, the implicit limit state function and its derivatives for slope stability analysis were approximated by the GP model with the explicit formulation. Furthermore, an iterative algorithm was presented to improve the precision of approximation of the limit state function at the region near the design point which contributes significantly to the failure probability. Results of four case studies including one nonslope and three slope problems indicate that the proposed method is more efficient to achieve reasonable accuracy for slope reliability analysis than the traditional RSM.
Databáze: Directory of Open Access Journals
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