Results 31 to 40 of about 2,317,544 (334)
Aerodynamic Design Based on Global Sensitivity Analysis Method [PDF]
Xibei Gongye Daxue Xuebao, 2018 To deal with the problem of the difficult optimization search and expensive computational cost caused by large-scale design variables, the hierarchical optimization design system based on the global sensitivity analysis method is established in this ...
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Global Sensitivity Analysis for Optimization with Variable Selection [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2019 The optimization of high dimensional functions is a key issue in engineering problems but it frequently comes at a cost that is not acceptable since it usually involves a complex and expensive computer code. Engineers often overcome this limitation by first identifying which parameters drive the most the function variations: non-influential variables ...
Spagnol, Adrien +2 more
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Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea : factors affecting the biomass of fish and benthos [PDF]
, 2014 Comprehensive analysis of parameter and driver sensitivity is key to establishing the credibility of models of complex systems. This is especially so for models of natural systems where experimental manipulation of the real-world to provide controlled ...
Cameron, Angus +3 more
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Lift-up, Kelvin-Helmholtz and Orr mechanisms in turbulent jets [PDF]
, 2020 Three amplification mechanisms present in turbulent jets, namely lift-up, Kelvin–Helmholtz and Orr, are characterized via global resolvent analysis and spectral proper orthogonal decomposition (SPOD) over a range of Mach numbers.
Cavalieri, André V. G. +5 more
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Sobol tensor trains for global sensitivity analysis [PDF]
Reliability Engineering & System Safety, 2019 Sobol indices are a widespread quantitative measure for variance-based global sensitivity analysis, but computing and utilizing them remains challenging for high-dimensional systems. We propose the tensor train decomposition (TT) as a unified framework for surrogate modeling and global sensitivity analysis via Sobol indices.
Ballester-Ripoll, Rafael +2 more
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Global sensitivity analysis of asymmetric energy harvesters
Nonlinear Dynamics, 2022 Parametric variability is inevitable in actual energy harvesters. It can significantly affect crucial aspects of the system performance, especially in harvesting systems that present geometric parameters, material properties, or excitation conditions that are susceptible to small perturbations. This work aims to develop an investigation to identify the
João Pedro Norenberg +3 more
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Quantile-oriented global sensitivity analysis of design resistance
Journal of Civil Engineering and Management, 2019 The article investigates the application of a new type of global quantile-oriented sensitivity analysis (called QSA in the article) and contrasts it with established Sobol’ sensitivity analysis (SSA). Comparison of QSA of the resistance design value (0.1
Zdeněk Kala
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Optimizing Genetic Circuits by Global Sensitivity Analysis [PDF]
Biophysical Journal, 2004 Artificial genetic circuits are becoming important tools for controlling cellular behavior and studying molecular biosystems. To genetically optimize the properties of complex circuits in a practically feasible fashion, it is necessary to identify the best genes and/or their regulatory components as mutation targets to avoid the mutation experiments ...
Herschel Rabitz +5 more
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Global sensitivity analysis of computer models with functional inputs [PDF]
, 2007 Global sensitivity analysis is used to quantify the influence of uncertain input parameters on the response variability of a numerical model. The common quantitative methods are applicable to computer codes with scalar input variables. This paper aims to
Iooss, Bertrand, Ribatet, Mathieu
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Global sensitivity analysis with dependence measures [PDF]
Journal of Statistical Computation and Simulation, 2014 Global sensitivity analysis with variance-based measures suffers from several theoretical and practical limitations, since they focus only on the variance of the output and handle multivariate variables in a limited way. In this paper, we introduce a new class of sensitivity indices based on dependence measures which overcomes these insufficiencies ...
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