Pages that link to "Item:Q2020995"

The following pages link to An efficient Kriging based method for time-dependent reliability based robust design optimization via evolutionary algorithm (Q2020995):

Displaying 18 items.

• Time-dependent reliability-based design optimization utilizing nonintrusive polynomial chaos (Q364416) (← links)
• A decoupling approach for time-dependent robust optimization with application to power semiconductor devices (Q821765) (← links)
• Time-dependent reliability-based design optimization with probabilistic and interval uncertainties (Q1988948) (← links)
• A novel time-dependent system constraint boundary sampling technique for solving time-dependent reliability-based design optimization problems (Q2020916) (← links)
• An envelope-function-based algorithm for time-dependent reliability analysis of structures with hybrid uncertainties (Q2110045) (← links)
• Advanced solution strategies for time-dependent reliability based design optimization (Q2180435) (← links)
• A novel nested stochastic Kriging model for response noise quantification and reliability analysis (Q2237444) (← links)
• A stochastic process discretization method combing active learning Kriging model for efficient time-variant reliability analysis (Q2237485) (← links)
• On the use of probabilistic and non-probabilistic super parametric hybrid models for time-variant reliability analysis (Q2246317) (← links)
• Efficient structural reliability analysis based on adaptive Bayesian support vector regression (Q2246408) (← links)
• A novel hybrid adaptive kriging and water cycle algorithm for reliability-based design and optimization strategy: application in offshore wind turbine monopile (Q6097650) (← links)
• Optimum-pursuing method for constrained optimization and reliability-based design optimization problems using kriging model (Q6153846) (← links)
• PINN-FORM: a new physics-informed neural network for reliability analysis with partial differential equation (Q6171227) (← links)
• SS-MASVM: an advanced technique for assessing failure probability of high-dimensional complex systems using the multi-class adaptive support vector machine (Q6201155) (← links)
• AK-Gibbs: an active learning kriging model based on Gibbs importance sampling algorithm for small failure probabilities (Q6550157) (← links)
• Expected lifetime prediction for time- and space-dependent structural systems based on active learning surrogate model (Q6588308) (← links)
• Time-variant reliability-based robust optimization for structures with material degradation (Q6641868) (← links)
• Variational Bayesian surrogate modelling with application to robust design optimisation (Q6643588) (← links)