Results 11 to 20 of about 1,085 (180)
Optimized sparse polynomial chaos expansion with entropy regularization [PDF]
Advances in Aerodynamics, 2022 Sparse Polynomial Chaos Expansion (PCE) is widely used in various engineering fields to quantitatively analyse the influence of uncertainty, while alleviating the problem of dimensionality curse.
Sijie Zeng +3 more
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Polynomial Chaos Expansion Approach to Interest Rate Models [PDF]
Journal of Probability and Statistics, 2015 The Polynomial Chaos Expansion (PCE) technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of ...
Luca Di Persio +2 more
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Physics-informed polynomial chaos expansions
Journal of Computational Physics, 2023 Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the known physics of the model.
Lukás Novák +2 more
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HIERARCHICAL ADAPTIVE POLYNOMIAL CHAOS EXPANSIONS [PDF]
Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015), 2015 Polynomial chaos expansions (PCE) are widely used in the framework of uncertainty quantification. However, when dealing with high dimensional complex problems, challenging issues need to be faced. For instance, high-order polynomials may be required, which leads to a large polynomial basis whereas usually only a few of the basis functions are in fact ...
Mai, Chu V., Sudret, Bruno
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Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2021 Sparse polynomial chaos expansions (PCE) are a popular surrogate modelling method that takes advantage of the properties of PCE, the sparsity-of-effects principle, and powerful sparse regression solvers to approximate computer models with many input parameters, relying on only few model evaluations.
Nora Lüthen +2 more
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Projection Pursuit Adaptation on Polynomial Chaos Expansions
Computer Methods in Applied Mechanics and Engineering, 2022 The present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities
Xiaoshu Zeng, Roger Ghanem
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Mechanics & Industry, 2023 Surface response models, such as polynomial chaos Expansion, are commonly used to deal with the case of uncertain input parameters. Such models are only surrogates, so it is necessary to develop tools to assess the level of error between the reference ...
Serra Quentin, Florentin Eric
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Compressive sensing adaptation for polynomial chaos expansions [PDF]
Journal of Computational Physics, 2019 Submitted to Journal of Computational ...
Panagiotis Tsilifis +7 more
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Performance of non-intrusive uncertainty quantification in the aeroservoelastic simulation of wind turbines [PDF]
Wind Energy Science, 2019 The present paper characterizes the performance of non-intrusive uncertainty quantification methods for aeroservoelastic wind turbine analysis. Two different methods are considered, namely non-intrusive polynomial chaos expansion and Kriging.
P. Bortolotti +4 more
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Comments on Truncation Errors for Polynomial Chaos Expansions [PDF]
IEEE Control Systems Letters, 2018 6 pages, 4 ...
Mühlpfordt, Tillmann +3 more
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