Pages that link to "Item:Q2790294"

The following pages link to Response surface methodology. Process and product optimization using designed experiments (Q2790294):

Displaying 50 items.

• Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics (Q324324) (← links)
• Optimization of probabilistic multiple response surfaces (Q437889) (← links)
• CFD study on laminar mixing at a very low Reynolds number by pitching and heaving a square cylinder (Q1649887) (← links)
• Removal of the points that do not support an \(E\)-optimal experimental design (Q1726897) (← links)
• Multi-objective optimization of peel and shear strengths in ultrasonic metal welding using machine learning-based response surface methodology (Q1979603) (← links)
• A parametric and non-intrusive reduced order model of car crash simulation (Q1986202) (← links)
• Surrogate optimization of deep neural networks for groundwater predictions (Q2046338) (← links)
• Improved multiobjective differential evolution with spherical pruning algorithm for optimizing 3D printing technology parametrization process (Q2108804) (← links)
• Approximate \(I\)-optimal designs for polynomial models over the unit ball (Q2123281) (← links)
• Augmented orthogonal uniform composite designs for fitting third-order model (Q2136066) (← links)
• Data-driven prognostic model for temperature field in additive manufacturing based on the high-fidelity thermal-fluid flow simulation (Q2138688) (← links)
• Multivariate steepest ascent method based on latent variables (Q2241722) (← links)
• Estimating parameter and discretization uncertainties using a laminar-turbulent transition model (Q2245551) (← links)
• Computation of the corrected Cornish-Fisher expansion using the response surface methodology: application to \textit{VaR} and \textit{CVaR} (Q2288917) (← links)
• \(\mathrm{SO}(3)\)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials (Q2309352) (← links)
• Process optimization. A statistical approach. (Q2641928) (← links)
• Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic models (Q2676029) (← links)
• Risk bounds when learning infinitely many response functions by ordinary linear regression (Q2686603) (← links)
• RSM based design optimization (Q2746138) (← links)
• A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments (Q3304857) (← links)
• A Multidisciplinary Approach for Optimization Design of CNC Machine Tools (Q3383758) (← links)
• (Q4264754) (← links)
• AN APPROACH TO OPTIMIZATION IN RESPONSE SURFACE METHODOLOGY (Q4540626) (← links)
• Bayesian design of experiments for logistic regression to evaluate multiple nuclear forensic algorithms (Q4627113) (← links)
• Correlation coefficient of response variances in compound noise and product array experiments (Q4638738) (← links)
• Response Surfaces for Overdispersion in the Study of the Conditions for Fish Eggs Hatching (Q4666533) (← links)
• How to Host An Effective Data Competition: Statistical Advice for Competition Design and Analysis (Q4970256) (← links)
• Number of DoE Required for Estimating Different Quality Surrogate (Q5057696) (← links)
• Sequential asymmetric third order rotatable designs (SATORDs) (Q5073404) (← links)
• Prediction variance of a central composite design with missing observation (Q5078084) (← links)
• Dual response surface optimization using a process “capability” index (Q5104506) (← links)
• (Q5476854) (← links)
• Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations (Q5864754) (← links)
• A Shiny Update to an Old Experiment Game (Q5869254) (← links)
• Orthogonal Minimally Aliased Response Surface Designs for Three-Level Quantitative Factors and Two-Level Categorical Factors (Q6039861) (← links)
• Sequencing mixed-model assembly lines with demand management: problem development and efficient multi-objective algorithms (Q6047979) (← links)
• Branch-and-Model: a derivative-free global optimization algorithm (Q6097758) (← links)
• Synergy frontier of multi-factor stock selection model (Q6105959) (← links)
• Best-worst tradeoff method (Q6122294) (← links)
• Robust parameter design of mixed multiple responses based on a latent variable Gaussian process model (Q6151477) (← links)
• Metamodel-based simulation optimization considering a single stochastic constraint (Q6164616) (← links)
• Graphical evaluation of prediction capability when the number of noise variable increases in robust parameter design (Q6164728) (← links)
• Practical efficient alpha: Encompassing all alphas of central composite design (Q6171888) (← links)
• Sparse POD modal subsets for reduced-order nonlinear explicit dynamics (Q6497683) (← links)
• Incremental Huber-Support vector regression based online robust parameter design (Q6541123) (← links)
• Run order consideration for sequential third order rotatable designs (Q6553007) (← links)
• Adaptive multi-surrogate-based constrained optimization method and its application (Q6554058) (← links)
• Multi-fidelity analysis and uncertainty quantification of beam vibration using correction response surfaces (Q6572348) (← links)
• Simultaneous model change detection in multivariate linear regression with application to Indonesian economic growth data (Q6577837) (← links)
• Inferential aspects for the optimal selection of the control parameters in Taguchi method (Q6579678) (← links)