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基于调相机制的航天器碰撞规避策略设计.
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- Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao, 2024, v. 63, n. 4, p. 97, doi. 10.13471/j.cnki.acta.snus.ZR20240025
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Influence of delamination on uncertain dynamic characteristics of variable angle tow laminates using polynomial neural network.
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- Acta Mechanica, 2024, v. 235, n. 9, p. 5789, doi. 10.1007/s00707-024-04019-5
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Twist Angle Error Statistical Analysis and Uncertain Influence on Aerodynamic Performance of Three-Dimensional Compressor Rotor.
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- Aerospace (MDPI Publishing), 2024, v. 11, n. 8, p. 614, doi. 10.3390/aerospace11080614
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Data‐driven modeling for fatigue loads of large‐scale wind turbines under active power regulation.
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- Wind Energy, 2021, v. 24, n. 6, p. 558, doi. 10.1002/we.2589
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Surrogate models for parameterized representation of wake‐induced loads in wind farms.
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- Wind Energy, 2019, v. 22, n. 10, p. 1371, doi. 10.1002/we.2362
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Uncertainty quantification of infinite aligned wind farm performance using non-intrusive polynomial chaos and a distributed roughness model.
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- Wind Energy, 2017, v. 20, n. 6, p. 945, doi. 10.1002/we.2072
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Issue Information.
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- Wind Energy, 2017, v. 20, n. 6, p. 943, doi. 10.1002/we.2042
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- Article
Uncertainty quantification in the calibration of numerical elements in nonlinear seismic analysis.
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- Earthquake Engineering & Structural Dynamics, 2022, v. 51, n. 12, p. 3000, doi. 10.1002/eqe.3711
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Model updating method for hybrid simulation based on global sensitivity analysis.
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- Earthquake Engineering & Structural Dynamics, 2021, v. 50, n. 14, p. 3792, doi. 10.1002/eqe.3533
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Modeling of spatial permittivity variations using Karhunen–Loève expansion for stochastic electromagnetic problems.
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- International Journal of RF & Microwave Computer-Aided Engineering, 2022, v. 32, n. 9, p. 1, doi. 10.1002/mmce.23250
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A comparison of techniques for finding coefficients of polynomial chaos models for antenna problems.
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- International Journal of RF & Microwave Computer-Aided Engineering, 2021, v. 31, n. 8, p. 1, doi. 10.1002/mmce.22729
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Robust multiscale optimization accounting for spatially-varying material uncertainties.
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- Structural & Multidisciplinary Optimization, 2022, v. 65, n. 2, p. 1, doi. 10.1007/s00158-021-03104-w
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A maximum cost-performance sampling strategy for multi-fidelity PC-Kriging.
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- Structural & Multidisciplinary Optimization, 2021, v. 64, n. 6, p. 3381, doi. 10.1007/s00158-021-02994-0
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A general integrated procedure for uncertainty-based design optimization of multilevel systems by hierarchical decomposition framework.
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- Structural & Multidisciplinary Optimization, 2021, v. 64, n. 4, p. 2669, doi. 10.1007/s00158-021-03021-y
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Structural uncertainty analysis with the multiplicative dimensional reduction–based polynomial chaos expansion approach.
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- Structural & Multidisciplinary Optimization, 2021, v. 64, n. 4, p. 2409, doi. 10.1007/s00158-021-02996-y
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Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data.
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- Structural & Multidisciplinary Optimization, 2021, v. 64, n. 2, p. 829, doi. 10.1007/s00158-021-02895-2
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An adaptive PCE-HDMR metamodeling approach for high-dimensional problems.
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- Structural & Multidisciplinary Optimization, 2021, v. 64, n. 1, p. 141, doi. 10.1007/s00158-021-02866-7
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Robust design optimization under dependent random variables by a generalized polynomial chaos expansion.
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- Structural & Multidisciplinary Optimization, 2021, v. 63, n. 5, p. 2425, doi. 10.1007/s00158-020-02820-z
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A sequential optimization framework for simultaneous design variables optimization and probability uncertainty allocation.
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- Structural & Multidisciplinary Optimization, 2021, v. 63, n. 3, p. 1307, doi. 10.1007/s00158-020-02759-1
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An efficient polynomial chaos-enhanced radial basis function approach for reliability-based design optimization.
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- Structural & Multidisciplinary Optimization, 2021, v. 63, n. 2, p. 789, doi. 10.1007/s00158-020-02730-0
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Design sensitivity analysis with polynomial chaos for robust optimization.
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- Structural & Multidisciplinary Optimization, 2021, v. 63, n. 1, p. 357, doi. 10.1007/s00158-020-02704-2
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A data-driven polynomial chaos method considering correlated random variables.
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- Structural & Multidisciplinary Optimization, 2020, v. 62, n. 4, p. 2131, doi. 10.1007/s00158-020-02602-7
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An adaptive polynomial chaos expansion for high-dimensional reliability analysis.
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- Structural & Multidisciplinary Optimization, 2020, v. 62, n. 4, p. 2051, doi. 10.1007/s00158-020-02594-4
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Hybrid metamodel of radial basis function and polynomial chaos expansions with orthogonal constraints for global sensitivity analysis.
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- Structural & Multidisciplinary Optimization, 2020, v. 62, n. 2, p. 597, doi. 10.1007/s00158-020-02516-4
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Probabilistic analytical target cascading using kernel density estimation for accurate uncertainty propagation.
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- Structural & Multidisciplinary Optimization, 2020, v. 61, n. 5, p. 2077, doi. 10.1007/s00158-019-02455-9
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Surrogate-assisted global sensitivity analysis: an overview.
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- Structural & Multidisciplinary Optimization, 2020, v. 61, n. 3, p. 1187, doi. 10.1007/s00158-019-02413-5
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A new uncertainty propagation method considering multimodal probability density functions.
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- Structural & Multidisciplinary Optimization, 2019, v. 60, n. 5, p. 1983, doi. 10.1007/s00158-019-02301-y
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Surrogate-assisted reliability-based design optimization: a survey and a unified modular framework.
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- Structural & Multidisciplinary Optimization, 2019, v. 60, n. 5, p. 2157, doi. 10.1007/s00158-019-02290-y
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Multi-fidelity uncertainty propagation using polynomial chaos and Gaussian process modeling.
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- Structural & Multidisciplinary Optimization, 2019, v. 60, n. 4, p. 1583, doi. 10.1007/s00158-019-02287-7
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Multivariate output global sensitivity analysis using multi-output support vector regression.
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- Structural & Multidisciplinary Optimization, 2019, v. 59, n. 6, p. 2177, doi. 10.1007/s00158-018-2184-z
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A gradient-based uncertainty optimization framework utilizing dimensional adaptive polynomial chaos expansion.
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- Structural & Multidisciplinary Optimization, 2019, v. 59, n. 4, p. 1199, doi. 10.1007/s00158-018-2123-z
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Structural reliability analysis based on analytical maximum entropy method using polynomial chaos expansion.
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- Structural & Multidisciplinary Optimization, 2018, v. 58, n. 3, p. 1187, doi. 10.1007/s00158-018-1961-z
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On efficient global optimization via universal Kriging surrogate models.
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- Structural & Multidisciplinary Optimization, 2018, v. 57, n. 6, p. 2377, doi. 10.1007/s00158-017-1867-1
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Reliability-based aeroelastic design of composite plate wings using a stability margin.
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- Structural & Multidisciplinary Optimization, 2018, v. 57, n. 4, p. 1695, doi. 10.1007/s00158-017-1838-6
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Optimisation of tensile membrane structures under uncertain wind loads using PCE and kriging based metamodels.
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- Structural & Multidisciplinary Optimization, 2018, v. 57, n. 3, p. 1149, doi. 10.1007/s00158-017-1802-5
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Sensitivity analysis based on non-intrusive regression-based polynomial chaos expansion for surgical mesh modelling.
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- Structural & Multidisciplinary Optimization, 2018, v. 57, n. 3, p. 1391, doi. 10.1007/s00158-017-1799-9
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Local bounds for singular Brascamp–Lieb forms with cubical structure.
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- Mathematische Zeitschrift, 2022, v. 302, n. 4, p. 2375, doi. 10.1007/s00209-022-03148-8
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Stochastic FDTD for stochastic problems with axial symmetry.
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- IET Microwaves, Antennas & Propagation (Wiley-Blackwell), 2023, v. 17, n. 2, p. 132, doi. 10.1049/mia2.12329
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A direct and analytical method for inverse problems under uncertainty in energy system design: combining inverse simulation and Polynomial Chaos theory.
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- Energy Informatics, 2024, v. 7, n. 1, p. 1, doi. 10.1186/s42162-024-00360-0
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ON GENERALIZED EULER NUMBERS AND POLYNOMIALS RELATED TO VALUES OF THE LERCH ZETA FUNCTION.
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- Integers: Electronic Journal of Combinatorial Number Theory, 2020, v. 20, p. 1
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Dynamic Optimisation of Beer Fermentation under Parametric Uncertainty.
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- Fermentation (Basel), 2021, v. 7, n. 4, p. 1, doi. 10.3390/fermentation7040285
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Uncertainty Quantification in SAR Induced by Ultra-High-Field MRI RF Coil via High-Dimensional Model Representation.
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- Bioengineering (Basel), 2024, v. 11, n. 7, p. 730, doi. 10.3390/bioengineering11070730
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Uncertainty quantification of large-eddy simulation results of riverine flows: a field and numerical study.
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- Environmental Fluid Mechanics, 2022, v. 22, n. 5, p. 1135, doi. 10.1007/s10652-022-09882-1
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Smolyak-Grid-Based Flutter Analysis with the Stochastic Aerodynamic Uncertainty.
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- Discrete Dynamics in Nature & Society, 2014, p. 1, doi. 10.1155/2014/174927
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Macro-Modeling of Electromagnetic Domains Exhibiting Geometric and Material Uncertainty.
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- Applied Computational Electromagnetics Society Journal, 2012, v. 27, n. 2, p. 80
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Scattering of radiofrequency waves by randomly modulated density interfaces in the edge of fusion plasmas.
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- Journal of Plasma Physics, 2021, v. 87, n. 4, p. 1, doi. 10.1017/S0022377821000647
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Polynomial chaos assessment of design tolerances for vortex-induced vibrations of two cylinders in tandem.
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- AI EDAM, 2017, v. 31, n. 2, p. 185, doi. 10.1017/S0890060417000075
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Fatigue Life Analysis of Vehicle Systems under Non-Gaussian Excitation.
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- International Journal of Automotive & Mechanical Engineering, 2020, v. 17, n. 2, p. 7956, doi. 10.15282/ijame.17.2.2020.14.0595
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Evolutionary and Sparse Regression Approach for Data-Driven Modelling of an Overhead Crane Dynamics.
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- Advances in Science & Technology Research Journal, 2024, v. 18, n. 4, p. 282, doi. 10.12913/22998624/189497
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A Novel Sparse Polynomial Expansion Method for Interval and Random Response Analysis of Uncertain Vibro-Acoustic System.
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- Shock & Vibration, 2021, p. 1, doi. 10.1155/2021/1125373
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