4.7 Article

A Sampling-Based Sensitivity Analysis Method Considering the Uncertainties of Input Variables and Their Distribution Parameters

Related references

Note: Only part of the references are listed.
Article Computer Science, Interdisciplinary Applications

Robust optimization of engineering structures involving hybrid probabilistic and interval uncertainties

Jin Cheng et al.

Summary: A novel robust optimization approach is proposed in this study for engineering structures with hybrid uncertainties, incorporating both stochastic and interval uncertain system parameters. The method utilizes generalized beta distribution to model stochastic system uncertainties and introduces the concept of interval angular vector to evaluate the robust feasibility of constraints. A genetic algorithm is presented to systematically solve the robust optimization problem and demonstrate its effectiveness through numerical and realistic engineering examples.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2021)

Article Engineering, Industrial

Local reliability based sensitivity analysis with the moving particles method

Carsten Proppe

Summary: The local reliability sensitivity methods aim to determine the partial derivatives of failure probability or reliability index with respect to model parameters. To avoid repeated evaluations of the performance function, an extension of the moving particles method is proposed for efficient local reliability sensitivity analysis. Additionally, a multilevel variant of the estimator is suggested to further reduce the variance and increase efficiency.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Article Engineering, Industrial

Variance-based sensitivity analysis: The quest for better estimators and designs between explorativity and economy

Samuele Lo Piano et al.

Summary: This study focuses on sample-based estimation procedures for total-effect sensitivity indices for independent inputs, aiming to achieve algorithmic improvement over existing best practices.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Review Engineering, Industrial

Random forests for global sensitivity analysis: A selective review

Anestis Antoniadis et al.

Summary: Understanding physical and engineering problems often requires running complex computational models with a high number of input variables. Global sensitivity analysis (GSA) methods help identify influential inputs, with meta-modeling and random forests providing efficient non-parametric approaches to sensitivity analysis. This allows for dimension reduction and effective quantification of variable importance, even in high-dimensional data sets.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Article Mathematics

Integration of Second-Order Sensitivity Method and CoKriging Surrogate Model

Zebin Zhang et al.

Summary: The cokriging method can enhance the accuracy of the surrogate model and reduce modeling time, but the high computational cost of high order derivatives poses a bottleneck for derivative enhanced methods.

MATHEMATICS (2021)

Article Computer Science, Interdisciplinary Applications

An efficient multi-objective optimization method based on the adaptive approximation model of the radial basis function

Xin Liu et al.

Summary: This method utilizes Latin hypercube design to obtain initial sample points, establishes approximation models using radial basis functions, and improves accuracy through reverse shape parameter analysis. It employs micro multi-objective genetic algorithm to solve Pareto optimal sets and enhances the ability to find accurate Pareto optimal sets using local-densifying approximation method.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2021)

Article Engineering, Mechanical

Non-Probabilistic Robust Equilibrium Optimization of Complex Uncertain Structures

Jin Cheng et al.

JOURNAL OF MECHANICAL DESIGN (2020)

Article Computer Science, Artificial Intelligence

A robust clustering algorithm using spatial fuzzy C-means for brain MR images

Madallah Alruwaili et al.

EGYPTIAN INFORMATICS JOURNAL (2020)

Article Engineering, Industrial

Multivariate sensitivity analysis: Minimum variance unbiased estimators of the first-order and total-effect covariance matrices

Matieyendou Lamboni

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Engineering, Multidisciplinary

Generalized sensitivity indices based on vector projection for multivariate output

Liyang Xu et al.

APPLIED MATHEMATICAL MODELLING (2019)

Article Engineering, Mechanical

A Bayesian Monte Carlo-based method for efficient computation of global sensitivity indices

Yicheng Zhou et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Industrial

An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression

M. Steiner et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Engineering, Industrial

Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions

Roland Schobi et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Computer Science, Interdisciplinary Applications

Multivariate output global sensitivity analysis using multi-output support vector regression

Kai Cheng et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2019)

Article Computer Science, Interdisciplinary Applications

Local analytical sensitivity analysis for design of continua with optimized 3D buckling behavior

Niels L. Pedersen et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2018)

Article Computer Science, Interdisciplinary Applications

Complete monotonic expression of the fourth-moment normal transformation for structural reliability

Yan-Gang Zhao et al.

COMPUTERS & STRUCTURES (2018)

Article Engineering, Industrial

A new method for model validation with multivariate output

Luyi Li et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2018)

Article Engineering, Civil

Reliability sensitivity estimation with sequential importance sampling

Iason Papaioannou et al.

STRUCTURAL SAFETY (2018)

Article Computer Science, Interdisciplinary Applications

Efficient global sensitivity analysis with correlated variables

Erin C. DeCarlo et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2018)

Article Statistics & Probability

Variance-based sensitivity analysis with the uncertainties of the input variables and their distribution parameters

Pan Wang et al.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION (2018)

Review Computer Science, Interdisciplinary Applications

Big Data in Experimental Mechanics and Model Order Reduction: Today's Challenges and Tomorrow's Opportunities

Jan Neggers et al.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2018)

Article Engineering, Industrial

A hybrid approach for global sensitivity analysis

Souvik Chakraborty et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2017)

Article Engineering, Industrial

Bayesian uncertainty quantification and propagation for validation of a microstructure sensitive model for prediction of fatigue crack initiation

Saikumar R. Yeratapally et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2017)

Article Computer Science, Interdisciplinary Applications

Variance-based sensitivity analysis for models with correlated inputs and its state dependent parameter solution

Luyi Li et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2017)

Article Computer Science, Interdisciplinary Applications

Temporal and spatial multi-parameter dynamic reliability and global reliability sensitivity analysis based on the extreme value moments

Yan Shi et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2017)

Article Computer Science, Interdisciplinary Applications

Unified uncertainty representation and quantification based on insufficient input data

Xiang Peng et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2017)

Article Engineering, Civil

An efficient sampling method for variance-based sensitivity analysis

Wanying Yun et al.

STRUCTURAL SAFETY (2017)

Article Engineering, Multidisciplinary

Optimal and reduced quadrature rules for tensor product and hierarchically refined splines in isogeometric analysis

Rene R. Hiemstra et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2017)

Article Computer Science, Interdisciplinary Applications

Robust optimization of uncertain structures based on normalized violation degree of interval constraint

Jin Cheng et al.

COMPUTERS & STRUCTURES (2017)

Article Engineering, Multidisciplinary

Optimal quadrature for univariate and tensor product splines

Kjetil Andre Johannessen

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2017)

Article Computer Science, Software Engineering

Gauss-Galerkin quadrature rules for quadratic and cubic spline spaces and their application to isogeometric analysis

Michael Barton et al.

COMPUTER-AIDED DESIGN (2017)

Article Computer Science, Interdisciplinary Applications

Global sensitivity analysis-enhanced surrogate (GSAS) modeling for reliability analysis

Zhen Hu et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2016)

Article Engineering, Multidisciplinary

Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

Michael Barton et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2016)

Review Management

Sensitivity analysis: A review of recent advances

Emanuele Borgonovo et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2016)

Article Engineering, Industrial

Uncertainty propagation and sensitivity analysis in system reliability assessment via unscented transformation

Claudio M. Rocco Sanseverino et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2014)

Article Engineering, Industrial

Variance-based sensitivity indices for models with dependent inputs

Thierry A. Mara et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2012)

Article Engineering, Industrial

Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data

Shankar Sankararaman et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2011)

Article Computer Science, Interdisciplinary Applications

Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index

Andrea Saltelli et al.

COMPUTER PHYSICS COMMUNICATIONS (2010)

Article Engineering, Industrial

Efficient computation of global sensitivity indices using sparse polynomial chaos expansions

Geraud Blatman et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2010)

Review Engineering, Industrial

Global sensitivity analysis using polynomial chaos expansions

Bruno Sudret

RELIABILITY ENGINEERING & SYSTEM SAFETY (2008)

Article Materials Science, Characterization & Testing

Advanced use of soft computing and eddy current test to evaluate mechanical integrity of metallic plates

Matteo Cacciola et al.

NDT & E INTERNATIONAL (2007)

Article Engineering, Industrial

Sensitivity analysis practices: Strategies for model-based inference

Andrea Saltelli et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2006)

Article Engineering, Industrial

Survey of sampling-based methods for uncertainty and sensitivity analysis

J. C. Helton et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2006)

Article Computer Science, Interdisciplinary Applications

Making best use of model evaluations to compute sensitivity indices

A Saltelli

COMPUTER PHYSICS COMMUNICATIONS (2002)