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Neural network-aided simulation of non-Gaussian stochastic processes · Study

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ArticleNeural network-aided simulation of non-Gaussian stochastic processes

Yang Li2023

Article2023

Neural network-aided simulation of non-Gaussian stochastic processes

Yang Li · Jun Xu

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

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Probabilistic and Robust Engineering Design Seismic Performance and Analysis Structural Health Monitoring Techniques

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References

1991Stochastic Finite Elements: A Spectral Approach 1972Digital simulation of random processes and its applications 1988Nonlinear Vibration Models for Extremes and Fatigue 2001Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes 2002Simulation of second-order processes using Karhunen–Loeve expansion 2011Advances of the probability density evolution method for nonlinear stochastic systems 2011Peak Factors for Non-Gaussian Load Effects Revisited 2011A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process

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2024Simulating non-stationary and non-Gaussian cross-correlated fields using multivariate Karhunen–Loève expansion and L-moments-based Hermite polynomial model 2025Simultaneous determination of stochastic dynamic responses and reliabilities for bilateral vibro-impact systems under colored noise excitation 2024An improved analytical solution to outcrossing rate for scalar nonstationary and non-gaussian processes

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Details

Year2023

Typearticle

Published2023-11-04

VenueReliability Engineering & System Safety

ISSN-L0951-8320

Languageen

Citations20

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.ress.2023.109786

openalex_workW4388336565

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