Pages that link to "Item:Q5940040"

The following pages link to A radial basis function method for global optimization (Q5940040):

Displaying 50 items.

• Proper orthogonal decomposition, surrogate modelling and evolutionary optimization in aerodynamic design (Q2015955) (← links)
• Modeling strength and failure variability due to porosity in additively manufactured metals (Q2020756) (← links)
• Computational design of innovative mechanical metafilters via adaptive surrogate-based optimization (Q2022061) (← links)
• Expected improvement for expensive optimization: a review (Q2022176) (← links)
• Global optimization via inverse distance weighting and radial basis functions (Q2023666) (← links)
• Surrogate optimization of deep neural networks for groundwater predictions (Q2046338) (← links)
• Global optimization based on active preference learning with radial basis functions (Q2051251) (← links)
• On the co-NP-completeness of the zonotope containment problem (Q2068561) (← links)
• GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration (Q2069161) (← links)
• Clustered active-subspace based local Gaussian process emulator for high-dimensional and complex computer models (Q2134712) (← links)
• Cluster Gauss-Newton method. An algorithm for finding multiple approximate minimisers of nonlinear least squares problems with applications to parameter estimation of pharmacokinetic models (Q2138298) (← links)
• Active preference-based optimization for human-in-the-loop feature selection (Q2157850) (← links)
• On the implementation of a global optimization method for mixed-variable problems (Q2165595) (← links)
• An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks (Q2180816) (← links)
• Deterministic global derivative-free optimization of black-box problems with bounded Hessian (Q2182783) (← links)
• Kriging-sparse polynomial dimensional decomposition surrogate model with adaptive refinement (Q2214537) (← links)
• A surrogate-based cooperative optimization framework for computationally expensive black-box problems (Q2218881) (← links)
• A local search method for costly black-box problems and its application to CSP plant start-up optimization refinement (Q2218908) (← links)
• Gradient-free strategies to robust well control optimization (Q2221181) (← links)
• A surrogate-based multiobjective metaheuristic and network degradation simulation model for robust toll pricing (Q2254186) (← links)
• Tuning BARON using derivative-free optimization algorithms (Q2274849) (← links)
• On the choice of the low-dimensional domain for global optimization via random embeddings (Q2301180) (← links)
• An improved hybrid-ORBIT algorithm based on point sorting and MLE technique (Q2326918) (← links)
• A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization (Q2342949) (← links)
• MISO: mixed-integer surrogate optimization framework (Q2357975) (← links)
• Integration of expert knowledge into radial basis function surrogate models (Q2358065) (← links)
• Derivative-free optimization: a review of algorithms and comparison of software implementations (Q2392129) (← links)
• Efficient global optimization algorithm assisted by multiple surrogate techniques (Q2392755) (← links)
• Examples of inconsistency in optimization by expected improvement (Q2393071) (← links)
• A quasi-multistart framework for global optimization of expensive functions using response surface models (Q2393073) (← links)
• Global optimization of non-convex piecewise linear regression splines (Q2399484) (← links)
• A stochastic adaptive radial basis function algorithm for costly black-box optimization (Q2422135) (← links)
• Using adaptive multi-accurate function evaluations in a surrogate-assisted method for computer experiments (Q2431347) (← links)
• Surrogate-based distributed optimisation for expensive black-box functions (Q2663899) (← links)
• Multi-fidelity cost-aware Bayesian optimization (Q2693418) (← links)
• Global Approximation for a Simulation Model Based onthe RBF Response Surface Set (Q2965070) (← links)
• A Recursive Local Polynomial Approximation Method Using Dirichlet Clouds and Radial Basis Functions (Q3186111) (← links)
• A novel sequential approximate optimization approach using data mining for engineering design optimization (Q3458843) (← links)
• The Bayesian Search Game (Q3459677) (← links)
• A hybrid one‐then‐two stage algorithm for computationally expensive electromagnetic design optimization (Q3591214) (← links)
• An efficient dynamical evolutionary algorithm for global optimization (Q4467339) (← links)
• An Efficient Approach for Reliability-Based Design Optimization Combined Sequential Optimization with Approximate Models (Q4563143) (← links)
• Finding global minima with a new dynamical evolutionary algorithm (Q4789543) (← links)
• (Q4967811) (← links)
• Optimal design of multivariate acceptance sampling plans by variables (Q5040527) (← links)
• Number of DoE Required for Estimating Different Quality Surrogate (Q5057696) (← links)
• Actor-Critic–Like Stochastic Adaptive Search for Continuous Simulation Optimization (Q5060521) (← links)
• Bifidelity Surrogate Modelling: Showcasing the Need for New Test Instances (Q5060781) (← links)
• Escaping local minima with local derivative-free methods: a numerical investigation (Q5093686) (← links)
• SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems (Q5131689) (← links)