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Adaptive virtual modelling enhanced dynamic and reliability analysis of SGPLRP-MEE plates
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Adaptive virtual modelling enhanced dynamic and reliability analysis of SGPLRP-MEE plates (2024)Adaptive virtual modelling enhanced dynam…AK-SYS-IE: A novel adaptive Kriging-based method for system reliability assessment combining information entropy (2024)AK-SYS-IE: A novel adaptive K…Active learning for structural reliability: Survey, general framework and benchmark (2022)Active learning for structura…Polyphase uncertainty analysis through virtual modelling technique (2021)Polyphase uncertainty analysi…Machine learning-based methods in structural reliability analysis: A review (2021)Machine learning-based method…Stochastic isogeometric analysis for the linear stability assessment of plate structures using a Kriging enhanced Neural Network (2020)Stochastic isogeometric analy…Meta-model based stochastic isogeometric analysis of composite plates (2020)Meta-model based stochastic i…Adaptive approaches in metamodel-based reliability analysis: A review (2020)Adaptive approaches in metamo…Machine learning aided stochastic structural free vibration analysis for functionally graded bar-type structures (2019)Machine learning aided stocha…AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)AK-MCS: An active learning re…Kriging metamodeling in simulation: A review (2007)Kriging metamodeling in simul…Stochastic Finite Elements: A Spectral Approach (1991)Structural Reliability Methods (1996)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)Metamodel-based importance sampling for structural reliability analysis (2013)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)Practical Bayesian Optimization of Machine Learning Algorithms (2012)Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment (2017)Mixed kernel function support vector regression for global sensitivity analysis (2017)Machine learning aided static structural reliability analysis for functionally graded frame structures (2019)Machine learning aided uncertainty quantification for engineering structures involving material-geometric randomness and data imperfection (2024)Structural reliability analysis using non-probabilistic convex model (2012)Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014)A new surrogate modeling technique combining Kriging and polynomial chaos expansions – Application to uncertainty analysis in computational dosimetry (2015)POLYNOMIAL-CHAOS-BASED KRIGING (2015)Statistics for Experimenters (1979)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A review and assessment of importance sampling methods for reliability analysis (2022)Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review (2023)Design and Analysis of Computer Experiments (1989)Bayesian Experimental Design: A Review (1995)Sensitivity analysis: A review of recent advances (2015)Fuzzy sets (1965)Fuzzy sets (1996)A virtual model architecture for engineering structures with Twin Extended Support Vector Regression (T-X-SVR) method (2021)Polymorphic uncertainty quantification for engineering structures via a hyperplane modelling technique (2022)Advanced virtual model assisted most probable point capturing method for engineering structures (2023)The intrinsic random functions and their applications (1973)Structural Reliability Analysis and Prediction (2017)An enhanced uniform simulation approach coupled with SVR for efficient structural reliability analysis (2023)A survey on machine learning approaches for uncertainty quantification of engineering systems (2025)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy (2024)Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions (2008)An improved approximate integral method for nonlinear reliability analysis (2024)Expected lifetime prediction for time- and space-dependent structural systems based on active learning surrogate model (2024)PLIC-FSR-SYS: System reliability analysis based on parallel learning of influential components with filtered sample region (2024)
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References

  • 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2,048 cited
  • 2007Kriging metamodeling in simulation: A review1,278 cited
  • 2021Machine learning-based methods in structural reliability analysis: A review370 cited
  • 2022Active learning for structural reliability: Survey, general framework and benchmark282 cited
  • 2020Adaptive approaches in metamodel-based reliability analysis: A review280 cited
  • 2019Machine learning aided stochastic structural free vibration analysis for functionally graded bar-type structures62 cited
  • 2024AK-SYS-IE: A novel adaptive Kriging-based method for system reliability assessment combining information entropy32 cited
  • 2021Polyphase uncertainty analysis through virtual modelling technique27 cited
  • 2020Meta-model based stochastic isogeometric analysis of composite plates19 cited
  • 2020Stochastic isogeometric analysis for the linear stability assessment of plate structures using a Kriging enhanced Neural Network16 cited

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