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ArticleLSTM-augmented deep networks for time-variant reliability assessment of dynamic systems

Mingyang Li2021

Article2021

LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems

Mingyang Li · Zequn Wang

48 citations·0/0 files stored·Reliability Engineering & System Safety

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Probabilistic and Robust Engineering Design Reliability and Maintenance Optimization Model Reduction and Neural Networks

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References

2003The PHI2 method: a way to compute time-variant reliability 2016A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis 2017A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis 2002Comparison of finite element reliability methods 2012A Nested Extreme Response Surface Approach for Time-Dependent Reliability-Based Design Optimization 2013Time-dependent reliability analysis with joint upcrossing rates 2018A general failure-pursuing sampling framework for surrogate-based reliability analysis 2017A hybrid relaxed first-order reliability method for efficient structural reliability analysis

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Details

Year2021

Typearticle

Published2021-09-27

VenueReliability Engineering & System Safety

ISSN-L0951-8320

Languageen

Citations48

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.ress.2021.108014

openalex_workW3202565730

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