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Simulation of Random Fields with Trend from Sparse Measurements without Detrending
8 references·4 citing·44 second hop
Simulation of Random Fields with Trend from Sparse Measurements without Detrending (2018)Simulation of Random Fields with Trend fr…Engineering Risk Assessment with Subset Simulation (2014)Engineering Risk Assessment w…The stochastic finite element method: Past, present and future (2008)The stochastic finite element…Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion (2005)Simulation of strongly non-Ga…Stochastic finite element analysis of shells with combined random material and geometric properties (2003)Stochastic finite element ana…Simulation of second-order processes using Karhunen–Loeve expansion (2002)Simulation of second-order pr…Effect of trends on detrended fluctuation analysis (2001)Effect of trends on detrended…Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes (2001)Convergence study of the trun…Random fields and stochastic finite elements (1986)Random fields and stochastic …Distribution-free P-box processes based on translation theory: Definition and simulation (2022)Distribution-free P-box proce…An active learning reliability analysis method using adaptive Bayesian compressive sensing and Monte Carlo simulation (ABCS-MCS) (2022)An active learning reliabilit…Uncertainty Quantification of Random Fields Based on Spatially Sparse Data by Synthesizing Bayesian Compressive Sensing and Stochastic Harmonic Function (2020)Uncertainty Quantification of…Statistical inference of random field auto-correlation structure from multiple sets of incomplete and sparse measurements using Bayesian compressive sampling-based bootstrapping (2019)Statistical inference of rand…Random Fields: Analysis and Synthesis (1983)Optimal Discretization of Random Fields (1993)Simulation of Multi-Dimensional Gaussian Stochastic Fields by Spectral Representation (1996)Assessment of spectral representation and Karhunen–Loève expansion methods for the simulation of Gaussian stochastic fields (2007)Spectral stochastic 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analysis using Support Vector Machines (2022)Prediction method of non-stationary random vibration fatigue reliability of turbine runner blade based on transfer learning (2023)An active learning method using deep adversarial autoencoder-based sufficient dimension reduction neural network for high-dimensional reliability analysis (2024)Sequential importance sampling for structural reliability analysis (2016)An efficient Kriging-based subset simulation method for hybrid reliability analysis under random and interval variables with small failure probability (2019)Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review (2023)
this work references cited by second hop

References

  • 2001Effect of trends on detrended fluctuation analysis1,285 cited
  • 2008The stochastic finite element method: Past, present and future999 cited
  • 2001Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes466 cited
  • 2014Engineering Risk Assessment with Subset Simulation315 cited
  • 1986Random fields and stochastic finite elements307 cited
  • 2002Simulation of second-order processes using Karhunen–Loeve expansion269 cited
  • 2005Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion259 cited
  • 2003Stochastic finite element analysis of shells with combined random material and geometric properties142 cited

Cited by

  • 2022An active learning reliability analysis method using adaptive Bayesian compressive sensing and Monte Carlo simulation (ABCS-MCS)64 cited
  • 2020Uncertainty Quantification of Random Fields Based on Spatially Sparse Data by Synthesizing Bayesian Compressive Sensing and Stochastic Harmonic Function30 cited
  • 2019Statistical inference of random field auto-correlation structure from multiple sets of incomplete and sparse measurements using Bayesian compressive sampling-based bootstrapping18 cited
  • 2022Distribution-free P-box processes based on translation theory: Definition and simulation16 cited

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