Handling noise and overfitting in surrogate models based on non-uniform rational basis spline entities

DOI10.1016/J.CMA.2024.116913MaRDI QIDQ6497149

Marco Montemurro, Ludovic Hallo, Bruno Vuillod, M Zani

Publication date: 6 May 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

noisesurrogate modelNURBSmetamodeloverfittinggradient-based optimisation

Mathematics Subject Classification ID

Numerical analysis (65-XX) Operations research, mathematical programming (90-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Recent advances and new challenges in the use of the proper generalized decomposition for solving multidimensional models
• Choosing nodes in parametric curve interpolation
• Computing the derivative of NURBS with respect to a knot
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• A general hybrid optimization strategy for curve fitting in the non-uniform rational basis spline framework
• Multiscale topology optimization using neural network surrogate models
• Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold
• Non-uniform rational basis spline hyper-surfaces for metamodelling
• Structural displacement requirement in a topology optimization algorithm based on isogeometric entities
• A Class of Globally Convergent Optimization Methods Based on Conservative Convex Separable Approximations
• Physics-informed deep learning for simultaneous surrogate modeling and PDE-constrained optimization of an airfoil geometry
• Multielement polynomial chaos kriging-based metamodelling for Bayesian inference of non-smooth systems

This page was built for publication: Handling noise and overfitting in surrogate models based on non-uniform rational basis spline entities