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An efficient surrogate-aided importance sampling framework for reliability analysis · Study

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ArticleAn efficient surrogate-aided importance sampling framework for reliability analysis

Wang-Sheng Liu2019

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Articlegreen2019

An efficient surrogate-aided importance sampling framework for reliability analysis

Wang-Sheng Liu · Sai Hung Cheung · Wen-Jun Cao

28 citations·0/0 files stored·Advances in Engineering Software

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Probabilistic and Robust Engineering Design Reliability and Maintenance Optimization Geotechnical Engineering and Analysis

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References

2016Simulation and the Monte Carlo Method 2007Simulation and the Monte Carlo Method 2001Estimation of small failure probabilities in high dimensions by subset simulation 1996Structural Reliability Methods 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation 2010Adaptive sparse polynomial chaos expansion based on least angle regression 1990A fast and efficient response surface approach for structural reliability problems 2008Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions

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2021An adaptive extreme learning machine based on an active learning method for structural reliability analysis 2022An innovative reliability-based design optimization method by combination of dual-stage adaptive kriging and genetic algorithm

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Details

Year2019

Typearticle

Published2019-07-04

VenueAdvances in Engineering Software

ISSN-L0965-9978

Languageen

Citations28

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.advengsoft.2019.102687

openalex_workW2955276804

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