Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling

DOI10.1016/j.matcom.2016.04.005OpenAlexW2346188849MaRDI QIDQ2228848

Shufang Song, Nilay Shah, Frank Lemke, Romain S. C. Lambert, Sergei Kucherenko

Publication date: 19 February 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2016.04.005

zbMATH Keywords

global sensitivity analysissobol indiceshigh dimensional model representationsgroup method of data handling

Mathematics Subject Classification ID

Statistics (62-XX) Operations research, mathematical programming (90-XX)

Related Items (2)

Modified GMDH-NN algorithm and its application for global sensitivity analysis ⋮ Global sensitivity analysis using support vector regression

Uses Software

• GUI-HDMR

Cites Work

• Unnamed Item
• Uncertainty management in simulation-optimization of complex systems. Algorithms and applications
• Sensitivity analysis: a review of recent advances
• High dimensional model representation for stochastic finite element analysis
• Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
• Adaptive sparse polynomial chaos expansion based on least angle regression
• Efficient input-output model representations
• GMDH algorithms for complex systems modelling
• Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
• An Unbiased Correlation Ratio Measure
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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