Journal ArticleDOI
Sparse polynomial chaos expansion based on Bregman-iterative greedy coordinate descent for global sensitivity analysis
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TLDR
A novel methodology for developing sparse PCE is proposed by making use of the efficiency of greedy coordinate descent in sparsity exploitation and the capability of Bregman iteration in accuracy enhancement, which shows that the proposed method is superior to the benchmark methods in terms of accuracy while maintaining a better balance among accuracy, complexity and computational efficiency.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2021-08-01. It has received 14 citations till now. The article focuses on the topics: Polynomial chaos & Coordinate descent.read more
Citations
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Journal ArticleDOI
An adaptive PCE-HDMR metamodeling approach for high-dimensional problems
TL;DR: The results show that the proposed PCE-HDMR has much superior accuracy and robustness in terms of both global and local error metrics while requiring fewer number of samples, and its superiority becomes more significant for polynomial-like functions, higher-dimensional problems, and relatively larger PCE degrees.
Journal ArticleDOI
Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion
TL;DR: In this paper , a prediction-oriented active sparse polynomial chaos expansion (PAS-PCE) is proposed for reliability analysis, which makes use of the Bregman-iterative greedy coordinate descent in effectively solving the least absolute shrinkage and selection operator based regression for sparse PCE approximation with a small set of initial samples.
Journal ArticleDOI
Robust topology optimization under material and loading uncertainties using an evolutionary structural extended finite element method
TL;DR: This paper is among the first to use the XFEM in studying the robust topology optimization under uncertainty and there is no need for any post-processing techniques, so the effectiveness of this method is justified by the clear and smooth boundaries obtained.
Journal ArticleDOI
A robust prediction method based on Kriging method and fuzzy c-means algorithm with application to a combine harvester
TL;DR: In this work, a robust prediction method is proposed based on the Kriging method and fuzzy c-means algorithm that produces much better performance in terms of outlier detection accuracy and prediction accuracy than the conventional outlier Detection method and the K Riging method.
Journal ArticleDOI
Blind-Kriging based natural frequency modeling of industrial Robot
TL;DR: In this article , a blind-Kriging-based natural frequency prediction of the industrial robot is proposed, utilizing the Latin Hypercube Sampling (LHS) technique, and a reliable dataset with 120 samples is generated for surrogate models based on the FEM.
References
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Journal ArticleDOI
Sparse polynomial chaos expansions for global sensitivity analysis with partial least squares and distance correlation
TL;DR: To overcome the influence of correlation in the construction of sparse PCE, a full PCE of model response is first developed based on partial least squares technique in the paper and an adaptive algorithm based on distance correlation is proposed to select influential basis polynomials.
Proceedings Article
Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization.
TL;DR: An improved convergence analysis of GCD for sparse optimization, and a formal analysis of its screening properties are presented, and an improved selection rule with stronger ability to produce sparse iterates is proposed.