Pages that link to "Item:Q5938386"

The following pages link to Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (Q5938386):

Displaying 50 items.

• An efficient dimension reduction for the Gaussian process emulation of two nested codes with functional outputs (Q2203403) (← links)
• Dynamics analysis of a hollow-shaft rotor system with an open crack under model uncertainties (Q2207776) (← links)
• Uncertainty quantification: a minimum variance unbiased (joint) estimator of the non-normalized Sobol' indices (Q2208405) (← links)
• A distributed active subspace method for scalable surrogate modeling of function valued outputs (Q2211746) (← links)
• Kriging-sparse polynomial dimensional decomposition surrogate model with adaptive refinement (Q2214537) (← links)
• On the use of derivatives in the polynomial chaos based global sensitivity and uncertainty analysis applied to the distributed parameter models (Q2214566) (← links)
• Risk of estimators for Sobol' sensitivity indices based on metamodels (Q2219226) (← links)
• Adaptive sparse polynomial dimensional decomposition for derivative-based sensitivity (Q2221403) (← links)
• Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (Q2222401) (← links)
• Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence (Q2222797) (← links)
• Bifurcation and sensitivity analysis reveal key drivers of multistability in a model of macrophage polarization (Q2225984) (← links)
• Derivative-based global sensitivity measures: general links with Sobol' indices and numerical tests (Q2227333) (← links)
• Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling (Q2228848) (← links)
• ANOVA method applied to proton exchange membrane fuel cell ageing forecasting using an echo state network (Q2228945) (← links)
• The ordering importance measure of random variable and its estimation (Q2229899) (← links)
• Global sensitivity analysis of a homogenized constrained mixture model of arterial growth and remodeling (Q2231105) (← links)
• Probabilistic uncertainty and sensitivity analysis of a vibratory-based actuation mechanism for a bio-inspired flapping-wing system (Q2234975) (← links)
• Quasi-Monte Carlo methods for two-stage stochastic mixed-integer programs (Q2235151) (← links)
• A variable-fidelity hybrid surrogate approach for quantifying uncertainties in the nonlinear response of braided composites (Q2237005) (← links)
• A generalized sensitivity analysis method based on variance and covariance decomposition of summatory functions for multi-input multi-output systems (Q2237728) (← links)
• Stochastic inverse modeling and parametric uncertainty of sediment deposition processes across geologic time scales (Q2238094) (← links)
• A hybrid decision support model using grey relational analysis and the additive-veto model for solving multicriteria decision-making problems: an approach to supplier selection (Q2241557) (← links)
• To Sobol or not to Sobol? The effects of sampling schemes in systems biology applications (Q2241935) (← links)
• Exploring the sensitivity in jellyfish locomotion under variations in scale, frequency, and duty cycle (Q2244905) (← links)
• On numerical uncertainties in scale-resolving simulations of canonical wall turbulence (Q2245432) (← links)
• Analysis and comparison of turbulence model coefficient uncertainty for canonical flow problems (Q2245436) (← links)
• Hemodynamics and stresses in numerical simulations of the thoracic aorta: stochastic sensitivity analysis to inlet flow-rate waveform (Q2245543) (← links)
• A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design (Q2246331) (← links)
• Application of sensitivity analysis and uncertainty quantification methods on the dynamic response of general nonlocal beams (Q2247274) (← links)
• Exploring the variance contributions of correlated model parameters: a sampling-based approach and its application in traffic simulation models (Q2247284) (← links)
• Modelling of the growth of a single bubble in semi-hard cheese, with experimental verification and sensitivity analysis (Q2281838) (← links)
• A new methodology based on covariance and HDMR for global sensitivity analysis (Q2282642) (← links)
• Multivariate function approximations using the D-MORPH algorithm (Q2285865) (← links)
• High frequency trading strategies, market fragility and price spikes: an agent based model perspective (Q2288938) (← links)
• Analytical variance based global sensitivity analysis for models with correlated variables (Q2290168) (← links)
• A generalized separation for the variance contributions of input variables and their distribution parameters (Q2290240) (← links)
• Sensitivity analysis of correlated inputs: application to a riveting process model (Q2292371) (← links)
• Global sensitivity analysis using support vector regression (Q2294004) (← links)
• Probabilistic modeling and global sensitivity analysis for CO\(_2\) storage in geological formations: a spectral approach (Q2294969) (← links)
• Borgonovo moment independent global sensitivity analysis by Gaussian radial basis function meta-model (Q2295081) (← links)
• Global sensitivity analysis for the design of nonlinear identification experiments (Q2296881) (← links)
• Mathematical prostate cancer evolution: effect of immunotherapy based on controlled vaccination strategy (Q2299972) (← links)
• Quantifying the uncertainty in a hyperelastic soft tissue model with stochastic parameters (Q2306756) (← links)
• Robust additive Gaussian process models using reference priors and cut-off-designs (Q2307104) (← links)
• Sequential sensitivity analysis of expensive black-box simulators with metamodelling (Q2308244) (← links)
• Calibration experimental design considering field response and model uncertainty (Q2309083) (← links)
• Accelerating Monte Carlo estimation with derivatives of high-level finite element models (Q2309798) (← links)
• Divide and conquer: an incremental sparsity promoting compressive sampling approach for polynomial chaos expansions (Q2309799) (← links)
• Efficient space-filling and near-orthogonality sequential Latin hypercube for computer experiments (Q2309986) (← links)
• A new non-intrusive polynomial chaos using higher order sensitivities (Q2310152) (← links)