Results 141 to 150 of about 53,557 (225)

mumpce_py: A Python Implementation of the Method of Uncertainty Minimization Using Polynomial Chaos Expansions. [PDF]

J Res Natl Inst Stand Technol, 2017
Sheen DA.
europepmc   +1 more source

Full-cycle prediction of crack healing in self-healing concrete using generalized polynomial chaos expansion. [PDF]

Commun Eng
Fu C, Xu W, Zhan Q, Chen C, Guo T, Zhang X, Pang B.   +6 more
europepmc   +1 more source

A Generalized Polynomial Chaos-Based Approach to Analyze the Impacts of Process Deviations on MEMS Beams. [PDF]

Sensors (Basel), 2017
Gao L, Zhou ZF, Huang QA.
europepmc   +1 more source

A comparison of Gaussian processes and polynomial chaos emulators in the context of haemodynamic pulse-wave propagation modelling. [PDF]

Philos Trans A Math Phys Eng Sci
Paun LM, Colebank MJ, Husmeier D.
europepmc   +1 more source

Global Reliability Sensitivity Analysis Based on Maximum Entropy and 2-Layer Polynomial Chaos Expansion. [PDF]

Entropy (Basel), 2018
Zhao J, Zeng S, Guo J, Du S.
europepmc   +1 more source

Parameters Variability Effects on Microstrip Interconnects via Hermite Polynomial Chaos [PDF]

, 2010
Canavero, Flavio, Manfredi, Paolo, Stievano, Igor Simone   +2 more
core   +1 more source

Exploiting Polynomial Chaos Expansion for Rapid Assessment of the Impact of Tissue Property Uncertainties in Low-Intensity Focused Ultrasound Stimulation. [PDF]

Bioelectromagnetics
Sumser K, Mestrom R, Tuysuz YE, Paulides MM.   +3 more
europepmc   +1 more source

Gaussian Processes and Polynomial Chaos Expansion for Regression Problem: Linkage via the RKHS and Comparison via the KL Divergence. [PDF]

Entropy (Basel), 2018
Yan L, Duan X, Liu B, Xu J.
europepmc   +1 more source

Parameters Variability Effects on Multiconductor Interconnects via Hermite Polynomial Chaos [PDF]

, 2011
Canavero, Flavio, Manfredi, Paolo, Stievano, Igor Simone   +2 more
core   +1 more source

Combining Polynomial Chaos Expansions and Kriging

, 2014
Computer simulation has emerged as a key tool for designing and assessing engineeringsystems in the last two decades. Uncertainty quantification has becomepopular more recently as a way to model all the uncertainties affecting the systemand their impact onto its performance.In this respect meta-models (a.k.a.
Schöbi, R., Kersaudy, P., Sudret, B., Wiart, J.   +3 more
openaire   +1 more source