Applied Mathematics
稀疏网格多项式混沌代理模型
Sparse grid polynomial chaos metamodelA numerical method for uncertainty quantification and sensitivity analysis that uses sparse grid quadrature to construct a surrogate model (metamodel) for complex systems, reducing computational cost compared to full tensor grids. / 一种用于不确定性量化和敏感性分析的数值方法,利用稀疏网格积分构建复杂系统的代理模型(元模型),相比全张量网格降低了计算成本。
- Knowledge type
- 数学理论
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-03 23:05:26
Sub-knowledge points
Uncertainty quantificationSensitivity analysisMetamodeling
Higher-order knowledge points
Polynomial chaos theorySparse grid quadratureUncertainty quantification methods
Main parameters and performance indicators
sparse grid level: Determines the resolution and accuracy of the quadrature pointspolynomial chaos expansion: Basis functions for representing the stochastic responsestraddle-type monorail vehicle system: The specific engineering system analyzed in the paper
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsEfficient uncertainty quantification and sensitivity analysis of straddle-type monorail vehicle system critical speed by sparse grid polynomial chaos metamodelOpen source
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1 recordsRecord title: Sparse grid polynomial chaos metamodel.
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