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Extremum selection method of random variable for nonlinear dynamic reliability analysis of turbine blade deformation
2 references·4 citing·20 second hop
Extremum selection method of random variable for nonlinear dynamic reliability analysis of turbine blade deformation (2012)Extremum selection method of random varia…Extremum response surface method of reliability analysis on two-link flexible robot manipulator (2012)Extremum response surface met…New Neural Network Response Surface Methods for Reliability Analysis (2011)New Neural Network Response S…Decomposed-Coordinated Framework With Enhanced Extremum Kriging for Multicomponent Dynamic Probabilistic Failure Analyses (2019)Decomposed-Coordinated Framew…Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM (2015)Optimum Control for Nonlinear…Dynamic probabilistic design for blade deformation with SVM-ERSM (2015)Dynamic probabilistic design …Nonlinear dynamic probabilistic design of turbine disk-radial deformation using extremum response surface method-based support vector machine of regression (2014)Nonlinear dynamic probabilist…A fast and efficient response surface approach for structural reliability problems (1990)A new look at the response surface approach for reliability analysis (1993)Application of kriging method to structural reliability problems (2004)Distributed collaborative extremum response surface method for mechanical dynamic assembly reliability analysis (2013)New neural network-based response surface method for reliability analysis of structures (2017)An adaptive artificial neural network for reliability analyses of complex engineering systems (2022)A comparison of approximate response functions in structural reliability analysis (2007)Adaptive explicit decision functions for probabilistic design and optimization using support vector machines (2008)Application of Least Squares Support Vector Machine for Regression to Reliability Analysis (2009)Reliability-Based Design Optimization Method of Turbine Disk with Transformed Deterministic Constraints (2016)Reliability-based structural optimization using neural networks and Monte Carlo simulation (2002)Novel method and model for dynamic reliability optimal design of turbine blade deformation (2014)Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling (2016)A new non-probabilistic time-dependent reliability model for mechanisms with interval uncertainties (2021)Use of Kriging Models to Approximate Deterministic Computer Models (2005)A Second-Order Reliability Method With First-Order Efficiency (2010)Improved Kriging with extremum response surface method for structural dynamic reliability and sensitivity analyses (2018)A Novel Reliability Analysis Approach With Collaborative Active Learning Strategy-Based Augmented RBF Metamodel (2020)Reliability Optimization of Structural Deformation with Improved Support Vector Regression Model (2020)Dynamic particle swarm optimization-radial function extremum neural network method of HCF probability analysis for compressor blade (2023)
this work references cited by second hop

References

  • 2012Extremum response surface method of reliability analysis on two-link flexible robot manipulator64 cited
  • 2011New Neural Network Response Surface Methods for Reliability Analysis44 cited

Cited by

  • 2015Dynamic probabilistic design for blade deformation with SVM-ERSM15 cited
  • 2019Decomposed-Coordinated Framework With Enhanced Extremum Kriging for Multicomponent Dynamic Probabilistic Failure Analyses12 cited
  • 2015Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM9 cited
  • 2014Nonlinear dynamic probabilistic design of turbine disk-radial deformation using extremum response surface method-based support vector machine of regression9 cited

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