Results 21 to 30 of about 53,557 (225)
Angular Correlation Using Rogers-Szegő-Chaos
Mathematics, 2020 Polynomial chaos expresses a probability density function (pdf) as a linear combination of basis polynomials. If the density and basis polynomials are over the same field, any set of basis polynomials can describe the pdf; however, the most logical ...
Christine Schmid, Kyle J. DeMars
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Frontiers in Physics, 2023 An efficient method of moments (MoM) based on polynomial chaos expansion (PCE) is applied to quickly calculate the electromagnetic scattering problems. The triangle basic functions are used to discretize the surface integral equations.
Xiaohui Yuan +5 more
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SeAr PC: Sensitivity enhanced arbitrary Polynomial Chaos
Computer Methods in Applied Mechanics and Engineering, 2023 This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme for sensitivity enhancement (1). Including available sensitivity information offers a way to mitigate the curse of dimensionality in Polynomial Chaos Expansions (PCEs ...
Nick Pepper +2 more
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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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Topics in Cognitive Science, EarlyView., 2023 Abstract Fractal fluctuations are a core concept for inquiries into human behavior and cognition from a dynamic systems perspective. Here, we present a generalized variance method for multivariate detrended fluctuation analysis (mvDFA). The advantage of this extension is that it can be applied to multivariate time series and considers intercorrelation ...
Sebastian Wallot +5 more
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Penerapan Algoritma Optimasi Chaos pada Jaringan Ridge Polynomial untuk Prediksi Jumlah Pengangguran
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2013 Abstrak Ridge polynomial neural network (RPNN) awalnya diusulkan oleh Shin dan Ghosh, dibangun dari jumlah peningkatan order pi-sigma neuron (PSN). RPNN mempertahankan pembelajaran cepat, pemetaan yang kuat dari layer tunggal higher order neural network
Rina Pramitasari, Retantyo Wardoyo
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Time‐Dependent Polynomial Chaos
AIP Conference Proceedings, 2008 Conventional generalized polynomial chaos is known to fail for long time integration, loosing its optimal convergence behaviour and developing unacceptable error levels. The reason for this loss of convergence is the assumption that the probability density function is constant in time.
Marc Gerritsma +2 more
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Non intrusive polynomial chaos-based stochastic macromodeling of multiport systems [PDF]
, 2014 We present a novel technique to efficiently perform the variability analysis of electromagnetic systems. The proposed method calculates a Polynomial Chaos-based macromodel of the system transfer function that includes its statistical properties.
Antonini, G +4 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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Airfoil Robust Optimization Based on Convolutional Neural Network and Polynomial Chaos Method
Hangkong gongcheng jinzhan, 2021 In conventional airfoil optimization design method, the aerodynamic performance of the optimal airfoil can deteriorate at the non-design point, so it is necessary to study the airfoil robust optimization method.An airfoil robustness design method based ...
GAO Yuan +4 more
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