Efficient reliability analysis based on deep learning-enhanced surrogate modelling and probability density evolution method
TLDR
Results demonstrate that the proposed AL-DLGPR-PDEM achieves a fair tradeoff between accuracy and efficiency for dealing with high-dimensional reliability problems in both static and dynamic analysis examples.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2022-01-01 and is currently open access. It has received 15 citations till now. The article focuses on the topics: Reliability (semiconductor) & Reliability (statistics).read more
Citations
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Journal ArticleDOI
Vectorial surrogate modeling method for multi-objective reliability design
TL;DR: In this article , a vectorial surrogate modeling (VSM) method is developed to synchronously establish an overall model of complex structures with multiple objectives, which can synchronously approximate to many limit state functions of reliability problems.
Journal ArticleDOI
Vectorial surrogate modeling approach for multi-failure correlated probabilistic evaluation of turbine rotor
Journal ArticleDOI
A GRU-based ensemble learning method for time-variant uncertain structural response analysis
TL;DR: In this article , a time-variant uncertain structural response analysis method is proposed based on recurrent neural network using gated recurrent units (GRU) combined with ensemble learning, by performing Latin hypercube sampling (LHS) of random variables, multiple GRU networks can be trained to estimate the time-varying system response under fixed random variables.
Journal ArticleDOI
An adaptive extreme learning machine based on an active learning method for structural reliability analysis
Jiaming Cheng,Hui Jin +1 more
TL;DR: In this study, an active learning reliability method is presented by the combination of the extreme learning machine (ELM) and an efficient sequential sampling method with the framework of the Bayesian optimization theory.
Journal ArticleDOI
Efficient framework for structural reliability analysis based on adaptive ensemble learning paired with subset simulation
TL;DR: In this article , an ensemble learning model which stacks six different classification machine/deep learning models is proposed to detect the structure condition (failure/safe) given structural parameters, external loads, and predefined safety thresholds.
References
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